Publications by authors named "Simon Rit"

46 Publications

Validation of proton dose calculation on scatter corrected 4D cone beam computed tomography using a porcine lung phantom.

Phys Med Biol 2021 08 30;66(17). Epub 2021 Aug 30.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.

Proton therapy treatment for lungs remains challenging as images enabling the detection of inter- and intra-fractional motion, which could be used for proton dose adaptation, are not readily available. 4D computed tomography (4DCT) provides high image quality but is rarely available in-room, while in-room 4D cone beam computed tomography (4DCBCT) suffers from image quality limitations stemming mostly from scatter detection. This study investigated the feasibility of using virtual 4D computed tomography (4DvCT) as a prior for a phase-per-phase scatter correction algorithm yielding a 4D scatter corrected cone beam computed tomography image (4DCBCT), which can be used for proton dose calculation. 4DCT and 4DCBCT scans of a porcine lung phantom, which generated reproducible ventilation, were acquired with matching breathing patterns. Diffeomorphic Morphons, a deformable image registration algorithm, was used to register the mid-position 4DCT to the mid-position 4DCBCT and yield a 4DvCT. The 4DCBCT was reconstructed using motion-aware reconstruction based on spatial and temporal regularization (MA-ROOSTER). Successively for each phase, digitally reconstructed radiographs of the 4DvCT, simulated without scatter, were exploited to correct scatter in the corresponding CBCT projections. The 4DCBCTwas then reconstructed with MA-ROOSTER using the corrected CBCT projections and the same settings and deformation vector fields as those already used for reconstructing the 4DCBCT. The 4DCBCTand the 4DvCT were evaluated phase-by-phase, performing proton dose calculations and comparison to those of a ground truth 4DCT by means of dose-volume-histograms (DVH) and gamma pass-rates (PR). For accumulated doses, DVH parameters deviated by at most 1.7% in the 4DvCT and 2.0% in the 4DCBCTcase. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCT), respectively. The 4DCBCTtechnique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans.
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http://dx.doi.org/10.1088/1361-6560/ac16e9DOI Listing
August 2021

Anthropomorphic lung phantom based validation of in-room proton therapy 4D-CBCT image correction for dose calculation.

Z Med Phys 2020 Nov 25. Epub 2020 Nov 25.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching, Germany. Electronic address:

Purpose: Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy.

Methods: Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (D, D, D, D) for the ITV, and by a 3D-gamma index analysis (global, 3%/3mm, 5Gy, 20Gy and 30Gy dose thresholds).

Results: Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV D, D, D and D for the 4D-CT and 4D-vCT-based dose distributions were -0.2%, 0.0%, -0.1% and -0.1%, respectively. Phase specific values varied between -0.5% and 0.2%, -0.2% and 0.5%, -3.5% and 1.5%, and -5.7% and 2.3%. The relative difference of accumulated D over the lungs was 2.3% and D for the phases varied between -5.4% and 5.8%. The gamma pass-rates with 5Gy, 20Gy and 30Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%.

Conclusions: Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation.
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http://dx.doi.org/10.1016/j.zemedi.2020.09.004DOI Listing
November 2020

The role of Monte Carlo simulation in understanding the performance of proton computed tomography.

Z Med Phys 2020 Aug 11. Epub 2020 Aug 11.

Department of Radiation Oncology, Department of Medical Physics, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium, (DKTK), Munich, Germany; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching b. München, Germany.

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail.
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http://dx.doi.org/10.1016/j.zemedi.2020.06.006DOI Listing
August 2020

Towards Monte Carlo simulation of X-ray phase contrast using GATE.

Opt Express 2020 May;28(10):14522-14535

We describe the first developments towards a Monte Carlo X-ray phase contrast imaging simulator for the medical imaging and radiotherapy simulation software GATE. Phase contrast imaging is an imaging modality taking advantage of the phase shift of X-rays. This modality produces images with a higher sensitivity than conventional, attenuation based imaging. As the first developments towards Monte Carlo phase contrast simulation, we implemented a Monte Carlo process for the refraction and total reflection of X-rays, as well as an analytical wave optics approach for generating Fresnel diffraction patterns. The implementation is validated against data acquired using a laboratory X-ray tomography system. The overall agreement between the simulations and the data is encouraging, which motivates further development of Monte Carlo based simulation of X-ray phase contrast imaging. These developments have been released in GATE version 8.2.
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http://dx.doi.org/10.1364/OE.391471DOI Listing
May 2020

A comparison of direct reconstruction algorithms in proton computed tomography.

Phys Med Biol 2020 06 1;65(10):105010. Epub 2020 Jun 1.

University of Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS, UMR 5220, U1206 F-69373, Lyon, France.

Several direct algorithms have been proposed to take into account the non-linear path of protons in the reconstruction of a proton CT (pCT) image. This paper presents a comparison between five of them, in terms of spatial resolution and relative stopping power (RSP) accuracy. Our comparison includes (1) a distance-driven algorithm extending the filtered backprojection to non-linear trajectories (DD), (2) an algorithm reconstructing a pCT image from optimized projections (ML), (3) a backproject-then-filter approach using a 2D cone filter (BTF), (4) a differentiated backprojection algorithm based on the inversion of the Hilbert transform (DBP), and (5) an algorithm using a 2D directional ramp filter (DR). We have simulated a single tracking pCT set-up using Geant4 through GATE, with a proton source and two position, direction and energy detectors upstream and downstream from the object. Tracker uncertainties were added on the position and direction measurements. A Catphan 528 phantom and a spiral phantom were simulated to measure the spatial resolution and a Gammex 467 phantom was used for the RSP accuracy. Each proton's trajectory was estimated using a most likely path (MLP) formalism. The spatial resolution was evaluated using the frequency corresponding to a modulation transfer function of 10% of its peak value and the RSP accuracy using the mean values in the inserts of the Gammex phantom. In terms of spatial resolution, it was shown that, for ideal trackers, the DR and BTF methods offer a slightly better resolution since each proton is directly binned in the image grid according to its MLP. However, all methods but the ML show comparable resolution when using realistic trackers. Regarding the RSP, three algorithms (DR, DD and BTF) show a mean relative error inside the inserts about 0.1%. As the DR and BTF methods are more computationally expensive, the DD-which allows the same spatial resolution in realistic conditions and the same accuracy-and the DBP-which has a fairly good accuracy (<0.2%) and allows reconstruction from truncated data-can be used for a reduced reconstruction time.
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http://dx.doi.org/10.1088/1361-6560/ab7d53DOI Listing
June 2020

Scatter Correction for Spectral CT Using a Primary Modulator Mask.

IEEE Trans Med Imaging 2020 06 29;39(6):2267-2276. Epub 2020 Jan 29.

The problem of scattered radiation correction in computed tomography (CT) is well known because scatter induces a bias, a loss of contrast and artifacts. Numerous strategies have been proposed in conventional CT (using energy-integrating detectors) but the problem is still open in the field of spectral CT, a new imaging technique based on energy-selective photon counting detectors. The aim of the present study is to introduce a scatter correction method adapted to multi-energy imaging and based on the use of a primary modulator mask. The main contributions are a correction matrix, which compensates for the effect of the mask, a scatter model based on B-splines and a cost function based on the mask structures and robust to the object structures. The performances of the method have been evaluated on both simulated and experimental data. The mean relative error was reduced from 20% in the lower energy-bins without correction to 4% with the proposed technique, which is close to the error caused by statistical noise.
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http://dx.doi.org/10.1109/TMI.2020.2970296DOI Listing
June 2020

SPARE: Sparse-view reconstruction challenge for 4D cone-beam CT from a 1-min scan.

Med Phys 2019 Sep 19;46(9):3799-3811. Epub 2019 Jul 19.

ACRF Image X Institute, University of Sydney, Sydney, NSW, Australia.

Purpose: Currently, four-dimensional (4D) cone-beam computed tomography (CBCT) requires a 3-4 min full-fan scan to ensure usable image quality. Recent advancements in sparse-view 4D-CBCT reconstruction have opened the possibility to reduce scan time and dose. The aim of this study is to provide a common framework for systematically evaluating algorithms for 4D-CBCT reconstruction from a 1-min scan. Using this framework, the AAPM-sponsored SPARE Challenge was conducted in 2018 to identify and compare state-of-the-art algorithms.

Methods: A clinically realistic CBCT dataset was simulated using patient CT volumes from the 4D-Lung database. The selected patients had multiple 4D-CT sessions, where the first 4D-CT was used as the prior CT, and the rest were used as the ground truth volumes for simulating CBCT projections. A GPU-based Monte Carlo tool was used to simulate the primary, scatter, and quantum noise signals. A total of 32 CBCT scans of nine patients were generated. Additional qualitative analysis was performed on a clinical Varian and clinical Elekta dataset to validate the simulation study. Participants were blinded from the ground truth, and were given 3 months to apply their reconstruction algorithms to the projection data. The submitted reconstructions were analyzed in terms of root-mean-squared-error (RMSE) and structural similarity index (SSIM) with the ground truth within four different region-of-interests (ROI) - patient body, lungs, planning target volume (PTV), and bony anatomy. Geometric accuracy was quantified as the alignment error of the PTV.

Results: Twenty teams participated in the challenge, with five teams completing the challenge. Techniques involved in the five methods included iterative optimization, motion-compensation, and deformation of the prior 4D-CT. All five methods rendered significant reduction in noise and streaking artifacts when compared to the conventional Feldkamp-Davis-Kress (FDK) algorithm. The RMS of the three-dimensional (3D) target registration error of the five methods ranged from 1.79 to 3.00 mm. Qualitative observations from the Varian and Elekta datasets mostly concur with those from the simulation dataset. Each of the methods was found to have its own strengths and weaknesses. Overall, the MA-ROOSTER method, which utilizes a 4D-CT motion model for temporal regularization, had the best and most consistent image quality and accuracy.

Conclusion: The SPARE Challenge represents the first framework for systematically evaluating state-of-the-art algorithms for 4D-CBCT reconstruction from a 1-min scan. Results suggest the potential for reducing scan time and dose for 4D-CBCT. The challenge dataset and analysis framework are publicly available for benchmarking future reconstruction algorithms.
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http://dx.doi.org/10.1002/mp.13687DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739166PMC
September 2019

Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy.

Phys Med Biol 2019 08 14;64(16):165002. Epub 2019 Aug 14.

Department of Medical Physics, Ludwig-Maximilians-Universität München, Garching b. München, Germany. Author to whom correspondence should be addressed.

Proton computed tomography (pCT) has been proposed as an alternative to x-ray computed tomography (CT) for acquiring relative to water stopping power (RSP) maps used for proton treatment planning dose calculations. In parallel, it has been shown that dual energy x-ray CT (DECT) improves RSP accuracy when compared to conventional single energy x-ray CT. This study aimed at directly comparing the RSP accuracy of both modalities using phantoms scanned at an advanced prototype pCT scanner and a state-of-the-art DECT scanner. Two phantoms containing 13 tissue-mimicking inserts of known RSP were scanned at the pCT phase II prototype and a latest generation dual-source DECT scanner (Siemens SOMATOM Definition FORCE). RSP accuracy was compared by mean absolute percent error (MAPE) over all inserts. A highly realistic Monte Carlo (MC) simulation was used to gain insight on pCT image artifacts which degraded MAPE. MAPE was 0.55% for pCT and 0.67% for DECT. The realistic MC simulation agreed well with pCT measurements ([Formula: see text]). Both simulation and experimental results showed ring artifacts in pCT images which degraded the MAPE compared to an ideal pCT simulation ([Formula: see text]). Using the realistic simulation, we could identify sources of artifacts, which are attributed to the interfaces in the five-stage plastic scintillator energy detector and calibration curve interpolation regions. Secondary artifacts stemming from the proton tracker geometry were also identified. The pCT prototype scanner outperformed a state-of-the-art DECT scanner in terms of RSP accuracy (MAPE) for plastic tissue mimicking inserts. Since artifacts tended to concentrate in the inserts, their mitigation may lead to further improvements in the reported pCT accuracy.
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http://dx.doi.org/10.1088/1361-6560/ab2b72DOI Listing
August 2019

In vivo gadolinium nanoparticle quantification with SPECT/CT.

EJNMMI Phys 2019 Jun 18;6(1). Epub 2019 Jun 18.

CREATIS-CNRS UMR 5220 - INSERM U1206 - Université Lyon 1 - INSA Lyon - Université Jean Monnet Saint-Etienne, Lyon, 69373, France.

Background: Gadolinium nanoparticles (Gd-NP) combined with radiotherapy are investigated for radiation dose enhancement in radiotherapy treatment. Indeed, NPs concentrated in a tumor could enhance its radiosensitization. The noninvasive quantification of the NP concentration is a crucial task for radiotherapy treatment planning and post-treatment monitoring as it will determine the absorbed dose. In this work, we evaluate the achievable accuracy of in vivo SPECT-based Gd-NP organ concentration on rats.

Methods: Gd-NPs were labeled with In radionuclide. SPECT images have been acquired on phantom and rats, with various Gd-NP injections. Images have been calibrated and corrected for attenuation, scatter, and partial volume effect. Image-based estimations were compared to both inductively coupled plasma mass spectrometer (ICP-MS) for Gd concentration and ex vivo organ activity measured by gamma counter.

Results: The accuracy for the Gd mass measurements in organ was within 10% for activity above 2 MBq or concentrations above ∼ 3-4 MBq/mL. The Gd mass calculation is based on In-Gd coefficient which defines the Gd detection limit. It was found to be in a range from 2 mg/MBq to 2 µg/MBq depending on the proportions of initial injection preparations. Measurement was also impaired by free Gd and In formed during metabolic processes.

Conclusions: Even if SPECT image quantification remains challenging mostly due to partial volume effect, this study shows that it has potential for the Gd mass measurements in organ. The main limitation of the method is its indirectness, and a special care should be taken if the organ of interest could be influenced by different clearance rate of free Gd and In formed by metabolic processes. We also discuss the practical aspects, potential, and limitations of Gd-NP in vivo image quantification with a SPECT.
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http://dx.doi.org/10.1186/s40658-019-0246-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582109PMC
June 2019

Effects of transverse heterogeneities on the most likely path of protons.

Phys Med Biol 2019 03 8;64(6):065003. Epub 2019 Mar 8.

Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69008, Lyon, France. Author to whom any correspondence should be addressed.

The use of a most likely path (MLP) formalism for protons to account for the effects of multiple Coulomb scattering has improved the spatial resolution in proton computed tomography (pCT). However, this formalism assumes a homogeneous medium and a continuous scattering of protons. In this paper, we quantify the path prediction error induced by transverse heterogeneities to assess whether correcting for such errors might improve the spatial resolution of pCT. To this end, we have tracked protons trajectories using Monte Carlo simulations in several phantoms with different heterogeneities. Our results show that transverse heterogeneities induce non Gaussian spatial distributions leading to errors in the prediction of the MLP, reaching 0.4 mm in a 20 cm wide simulated heterogeneity and 0.13 mm in a realistic phantom. It was also shown that when the spatial distributions have more than one peak, a most likely path, if any, has yet to be defined. Transverse heterogeneities also affect energy profiles, which could explain some of the artifacts described in other works and could make the energy cuts usually performed to exclude nuclear events less efficient.
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http://dx.doi.org/10.1088/1361-6560/ab02a8DOI Listing
March 2019

Technical Note: Relative proton stopping power estimation from virtual monoenergetic images reconstructed from dual-layer computed tomography.

Med Phys 2019 Apr 19;46(4):1821-1828. Epub 2019 Feb 19.

Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint-Étienne, CNRS, Inserm, CREATIS, UMR 5220, U1206, F-69373, Lyon, France.

Purpose: The objective of this technical note was to investigate the accuracy of proton stopping power relative to water (RSP) estimation using a novel dual-layer, dual-energy computed tomography (DL-DECT) scanner for potential use in proton therapy planning. DL-DECT allows dual-energy reconstruction from scans acquired at a single x-ray tube voltage V by using two-layered detectors.

Methods: Sets of calibration and evaluation inserts were scanned at a DL-DECT scanner in a custom phantom with variable diameter D (0 to 150 mm) at V of 120 and 140 kV. Inserts were additionally scanned at a synchrotron computed tomography facility to obtain comparative linear attenuation coefficients for energies from 50 to 100 keV, and reference RSP was obtained using a carbon ion beam and variable water column. DL-DECT monoenergetic (mono-E) reconstructions were employed to obtain RSP by adapting the Yang-Saito-Landry (YSL) method. The method was compared to reference RSP via the root mean square error (RMSE) over insert mean values obtained from volumetric regions of interest. The accuracy of intermediate quantities such as the relative electron density (RED), effective atomic number (EAN), and the mono-E was additionally evaluated.

Results: The lung inserts showed higher errors for all quantities and we report RMSE excluding them. RMSE for μ from DL-DECT mono-E was below 1.9%. For the evaluation inserts at D = 150 mm and V = 140 kV, RED RMSE was 1.0%, while for EAN it was 2.9%. RSP RMSE was below 0.8% for all D and V, which did not strongly affect the results.

Conclusions: In this investigation of RSP accuracy from DL-DECT, we have shown that RMSE below 1% can be achieved. It was possible to adapt the YSL method for DL-DECT and intermediate quantities RED and EAN had comparable accuracy to previous publications.
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http://dx.doi.org/10.1002/mp.13404DOI Listing
April 2019

Comparison of five one-step reconstruction algorithms for spectral CT.

Phys Med Biol 2018 Nov 22;63(23):235001. Epub 2018 Nov 22.

Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, Centre Léon Bérard, F-69373, Lyon, France.

Over the last decade, dual-energy CT scanners have gone from prototypes to clinically available machines, and spectral photon counting CT scanners are following. They require a specific reconstruction process, consisting of two steps: material decomposition and tomographic reconstruction. Image-based methods perform reconstruction, then decomposition, while projection-based methods perform decomposition first, and then reconstruction. As an alternative, 'one-step inversion' methods have been proposed, which perform decomposition and reconstruction simultaneously. Unfortunately, one-step methods are typically slower than their two-step counterparts, and in most CT applications, reconstruction time is critical. This paper therefore proposes to compare the convergence speeds of five one-step algorithms. We adapted all these algorithms to solve the same problem: spectral photon-counting CT reconstruction from five energy bins, using a three materials decomposition basis and spatial regularization. The paper compares a Bayesian method which uses non-linear conjugate gradient for minimization (Cai et al 2013 Med. Phys. 40 111916-31), three methods based on quadratic surrogates (Long and Fessler 2014 IEEE Trans. Med. Imaging 33 1614-26, Weidinger et al 2016 Int. J. Biomed. Imaging 2016 1-15, Mechlem et al 2018 IEEE Trans. Med. Imaging 37 68-80), and a primal-dual method based on MOCCA, a modified Chambolle-Pock algorithm (Barber et al 2016 Phys. Med. Biol. 61 3784). Some of these methods have been accelerated by using μ-preconditioning, i.e. by performing all internal computations not with the actual materials the object is made of, but with carefully chosen linear combinations of those. In this paper, we also evaluated the impact of three different μ-preconditioners on convergence speed. Our experiments on simulated data revealed vast differences in the number of iterations required to reach a common image quality objective: Mechlem et al (2018 IEEE Trans. Med. Imaging 37 68-80) needed ten iterations, Cai et al (2013 Med. Phys. 40 111916-31), Long and Fessler (2014 IEEE Trans. Med. Imaging 33 1614-26) and Weidinger et al (2016 Int. J. Biomed. Imaging 2016 1-15) several hundreds, and Barber et al (2016 Phys. Med. Biol. 61 3784) several thousands. We also sum up other practical aspects, like memory footprint and the need to tune extra parameters.
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http://dx.doi.org/10.1088/1361-6560/aaeaf2DOI Listing
November 2018

Feasibility of 4DCBCT-based proton dose calculation: An ex vivo porcine lung phantom study.

Z Med Phys 2019 Aug 14;29(3):249-261. Epub 2018 Nov 14.

Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Am Coulombwall 1, 85748 Garching, Germany. Electronic address:

Inter-fractional variations of breathing pattern and patient anatomy introduce dose uncertainties in proton therapy. One approach to monitor these variations is to utilize the cone-beam computed tomography (CT, CBCT) scans routinely taken for patient positioning, reconstruct them as 4DCBCTs, and generate 'virtual CTs' (vCTs), combining the accurate CT numbers of the diagnostic 4DCT and the geometry of the daily 4DCBCT by using deformable image registration (DIR). In this study different algorithms for 4DCBCT reconstruction and DIR were evaluated. For this purpose, CBCT scans of a moving ex vivo porcine lung phantom with 663 and 2350 projections respectively were acquired, accompanied by an additional 4DCT as reference. The CBCT projections were sorted in 10 phase bins with the Amsterdam-shroud method and reconstructed phase-by-phase using first a FDK reconstruction from the Reconstruction Toolkit (RTK) and again an iterative reconstruction algorithm implemented in the Gadgetron Toolkit. The resulting 4DCBCTs were corrected by DIR of the corresponding 4DCT phases, using both a morphons algorithm from REGGUI and a b-spline deformation from Plastimatch. The resulting 4DvCTs were compared to the 4DCT by visual inspection and by calculating water equivalent thickness (WET) maps from the phantom's surface to the distal edge of a target from various angles. The optimized procedure was successfully repeated with mismatched input phases and on a clinical patient dataset. Proton treatment plans were simulated on the 4DvCTs and the dose distributions compared to the reference based on the 4DCT via gamma pass rate analysis. A combination of iterative reconstruction and morphons DIR yielded the most accurate 4DvCTs, with median WET differences under 2mm and 3%/3mm gamma pass rates per phase between 89% and 99%. These results suggest that image correction of iteratively reconstructed 4DCBCTs with a morphons DIR of the planning CT may yield sufficiently accurate 4DvCTs for daily time resolved proton dose calculations.
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http://dx.doi.org/10.1016/j.zemedi.2018.10.005DOI Listing
August 2019

Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections.

Phys Med Biol 2018 10 24;63(21):215009. Epub 2018 Oct 24.

Department of Medical Physics, Ludwig-Maximilians-Universität München, 85748 Garching b. München, Germany. Authors contributed equally.

We present a formalism for two-dimensional (2D) noise reconstruction in proton computed tomography (pCT). This is necessary for the application of fluence modulated pCT (FMpCT) since it permits image noise prescription and the corresponding proton fuence optimization. We aimed at extending previously published formalisms to account for the impact of multiple Coulomb scattering (MCS) on projection noise, and the use of filtered back projection (FBP) reconstruction along curved paths with distance driven binning (DDB). 2D noise reconstruction for a beam of protons with parallel initial momentum vectors, and for projections binned both at the rear tracker and with DDB, was established. Monte Carlo (MC) simulations of pCT scans of a water cylinder were employed to generate pCT projections and to calculate their noise for use in 2D noise reconstruction. These were compared to results from an analytical model accounting for MCS for rear tracker binning as well as against the previously published central pixel model which ignores MCS. Image noise reconstructed with the formalism for rear tracker binning and DDB were compared to MC results using annular regions of interest (ROIs). Agreement better than 8% was obtained between the noise of projections calculated with MC simulation and our model. Noise from annular ROIs agreed with our noise reconstructions for rear tracker binning and DDB. The central pixel model ignoring MCS underestimated projection and thus image noise by up to 40% towards the object's edge. The use of DDB decreased the image noise towards the object's edge when compared to rear tracker binning and yielded more uniform noise throughout the image. MCS should not be neglected when predicting image noise for pixels away from the center of an object in a pCT scan due to the increasing influence of the gradient of the object's hull closer to the edges.
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http://dx.doi.org/10.1088/1361-6560/aae5c9DOI Listing
October 2018

Experimental fluence-modulated proton computed tomography by pencil beam scanning.

Med Phys 2018 Jul 8;45(7):3287-3296. Epub 2018 Jun 8.

Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching b. München, Germany.

Purpose: This experimental study is aimed at demonstrating, using a simple cylindrical water phantom, the feasibility of fluence-modulated proton computed tomography (FMpCT) by pencil beam scanning (PBS) proton computed tomography (pCT).

Methods: The phase II pCT prototype of the Loma Linda U. and U. C. Santa Cruz was operated using the PBS beam line of the Northwestern Medicine Chicago Proton Center. A 20 × 10 grid of 1.37 cm full width half maximum pencil beams (PB) equally spaced by 1 cm was used to acquire 45 projections in step and shoot mode. The PB pattern's fluence was modified to allow FMpCT scans with fluence modulation factors (FMF) of 50% and 20%. A central FMpCT region of interest (FMpCT-ROI) was used to define a high image quality region. Reconstructed images were evaluated in terms of relative stopping power (RSP) accuracy and noise using annular ROIs. The FMpCT dose savings were estimated by Monte Carlo (MC) simulation of the pCT acquisitions using beam phase space distributions. PBS pCT results with homogeneous fluence were additionally compared to broad beam results in terms of RSP accuracy and noise.

Results: PBS pCT scans with acceptable pileup were possible, and images were comparable to previously acquired broad beam pCT images in terms of both noise and accuracy. In the FMpCT-ROI, the noise and accuracy from full fluence (FF) scans were preserved. Dose savings of up to 60% were achieved at the object's edge when using FMF of 20%.

Conclusion: In this study, we have demonstrated that PBS pCT scans can achieve equivalent accuracy as those obtained from broad beams. The feasibility of FMpCT scans was demonstrated; image accuracy and noise were successfully preserved in the central FMpCT-ROI chosen for this study, and dose reduction of up to 60% at the object's edge was realized.
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http://dx.doi.org/10.1002/mp.12989DOI Listing
July 2018

Deriving the mean excitation energy map from dual-energy and proton computed tomography.

Phys Imaging Radiat Oncol 2018 Apr 26;6:20-24. Epub 2018 Apr 26.

Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Étienne, CNRS, INSERM, CREATIS UMR 5220, U1206, Centre Léon Bérard, F-69373 Lyon, France.

The mean excitation energy, , is an essential quantity for proton treatment planning. This work investigated the feasibility of extracting the spatial distribution of by combining two computed tomography (CT) modalities, dual-energy CT and proton CT, which provided the spatial distribution of the relative electron density and the stopping power relative to water, respectively. We provided the analytical derivation of as well as its uncertainty. Results were validated on simulated X-ray and proton CT images of a digital anthropomorphic phantom. Accuracy was below 15% with a large uncertainty, which demonstrated the potential and limits of the technique.
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http://dx.doi.org/10.1016/j.phro.2018.04.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7807613PMC
April 2018

Deformable image registration applied to lung SBRT: Usefulness and limitations.

Phys Med 2017 Dec 25;44:108-112. Epub 2017 Sep 25.

Univ Lyon, INSA-Lyon, Université Lyon 1, CNRS, Inserm, Centre Léon Bérard, CREATIS UMR 5220, U1206, F-69373 Lyon, France.

Radiation therapy (RT) of the lung requires deformation analysis. Deformable image registration (DIR) is the fundamental method to quantify deformations for various applications: motion compensation, contour propagation, dose accumulation, etc. DIR is therefore unavoidable in lung RT. DIR algorithms have been studied for decades and are now available both within commercial and academic packages. However, they are complex and have limitations that every user must be aware of before clinical implementation. In this paper, the main applications of DIR for lung RT with their associated uncertainties and their limitations are reviewed.
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http://dx.doi.org/10.1016/j.ejmp.2017.09.121DOI Listing
December 2017

Regularization of nonlinear decomposition of spectral x-ray projection images.

Med Phys 2017 Sep;44(9):e174-e187

Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, Lyon, U1206, F69621, France.

Purpose: Exploiting the x-ray measurements obtained in different energy bins, spectral computed tomography (CT) has the ability to recover the 3-D description of a patient in a material basis. This may be achieved solving two subproblems, namely the material decomposition and the tomographic reconstruction problems. In this work, we address the material decomposition of spectral x-ray projection images, which is a nonlinear ill-posed problem.

Methods: Our main contribution is to introduce a material-dependent spatial regularization in the projection domain. The decomposition problem is solved iteratively using a Gauss-Newton algorithm that can benefit from fast linear solvers. A Matlab implementation is available online. The proposed regularized weighted least squares Gauss-Newton algorithm (RWLS-GN) is validated on numerical simulations of a thorax phantom made of up to five materials (soft tissue, bone, lung, adipose tissue, and gadolinium), which is scanned with a 120 kV source and imaged by a 4-bin photon counting detector. To evaluate the method performance of our algorithm, different scenarios are created by varying the number of incident photons, the concentration of the marker and the configuration of the phantom. The RWLS-GN method is compared to the reference maximum likelihood Nelder-Mead algorithm (ML-NM). The convergence of the proposed method and its dependence on the regularization parameter are also studied.

Results: We show that material decomposition is feasible with the proposed method and that it converges in few iterations. Material decomposition with ML-NM was very sensitive to noise, leading to decomposed images highly affected by noise, and artifacts even for the best case scenario. The proposed method was less sensitive to noise and improved contrast-to-noise ratio of the gadolinium image. Results were superior to those provided by ML-NM in terms of image quality and decomposition was 70 times faster. For the assessed experiments, material decomposition was possible with the proposed method when the number of incident photons was equal or larger than 10 and when the marker concentration was equal or larger than 0.03 g·cm .

Conclusions: The proposed method efficiently solves the nonlinear decomposition problem for spectral CT, which opens up new possibilities such as material-specific regularization in the projection domain and a parallelization framework, in which projections are solved in parallel.
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http://dx.doi.org/10.1002/mp.12283DOI Listing
September 2017

Optimization of dual-energy CT acquisitions for proton therapy using projection-based decomposition.

Med Phys 2017 Sep 18;44(9):4548-4558. Epub 2017 Aug 18.

Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1206, INSA-Lyon, Université Lyon 1, Centre Léon Bérard, Lyon, France.

Purpose: Dual-energy computed tomography (DECT) has been presented as a valid alternative to single-energy CT to reduce the uncertainty of the conversion of patient CT numbers to proton stopping power ratio (SPR) of tissues relative to water. The aim of this work was to optimize DECT acquisition protocols from simulations of X-ray images for the treatment planning of proton therapy using a projection-based dual-energy decomposition algorithm.

Methods: We have investigated the effect of various voltages and tin filtration combinations on the SPR map accuracy and precision, and the influence of the dose allocation between the low-energy (LE) and the high-energy (HE) acquisitions. For all spectra combinations, virtual CT projections of the Gammex phantom were simulated with a realistic energy-integrating detector response model. Two situations were simulated: an ideal case without noise (infinite dose) and a realistic situation with Poisson noise corresponding to a 20 mGy total central dose. To determine the optimal dose balance, the proportion of LE-dose with respect to the total dose was varied from 10% to 90% while keeping the central dose constant, for four dual-energy spectra. SPR images were derived using a two-step projection-based decomposition approach. The ranges of 70 MeV, 90 MeV, and 100 MeV proton beams onto the adult female (AF) reference computational phantom of the ICRP were analytically determined from the reconstructed SPR maps.

Results: The energy separation between the incident spectra had a strong impact on the SPR precision. Maximizing the incident energy gap reduced image noise. However, the energy gap was not a good metric to evaluate the accuracy of the SPR. In terms of SPR accuracy, a large variability of the optimal spectra was observed when studying each phantom material separately. The SPR accuracy was almost flat in the 30-70% LE-dose range, while the precision showed a minimum slightly shifted in favor of lower LE-dose. Photon noise in the SPR images (20 mGy dose) had lower impact on the proton range accuracy as comparable results were obtained for the noiseless situation (infinite dose). Root-mean-square range errors averaged over all irradiation angles associated to dual-energy imaging were comprised between 0.50 mm and 0.72 mm for the noiseless situation and between 0.51 mm and 0.77 mm for the realistic scenario.

Conclusions: The impact of the dual-energy spectra and the dose allocation between energy levels on the SPR accuracy and precision determined through a projection-based dual-energy algorithm were evaluated to guide the choice of spectra for dual-energy CT for proton therapy. The dose balance between energy levels was not found to be sensitive for the SPR estimation. The optimal pair of dual-energy spectra was material dependent but on a heterogeneous anthropomorphic phantom, there was no significant difference in range accuracy and the choice of spectra could be driven by the precision, i.e., the energy gap.
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http://dx.doi.org/10.1002/mp.12448DOI Listing
September 2017

Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT.

Med Phys 2016 Oct;43(10):5635

Department of Medical Physics, Ludwig-Maximilians-Universität München, Garching bei München 85748, Germany.

Purpose: This work aims at investigating intensity corrected cone-beam x-ray computed tomography (CBCT) images for accurate dose calculation in adaptive intensity modulated proton therapy (IMPT) for prostate and head and neck (H&N) cancer. A deformable image registration (DIR)-based method and a scatter correction approach using the image data obtained from DIR as prior are characterized and compared on the basis of the same clinical patient cohort for the first time.

Methods: Planning CT (pCT) and daily CBCT data (reconstructed images and measured projections) of four H&N and four prostate cancer patients have been considered in this study. A previously validated Morphons algorithm was used for DIR of the planning CT to the current CBCT image, yielding a so-called virtual CT (vCT). For the first time, this approach was translated from H&N to prostate cancer cases in the scope of proton therapy. The warped pCT images were also used as prior for scatter correction of the CBCT projections for both tumor sites. Single field uniform dose and IMPT (only for H&N cases) treatment plans have been generated with a research version of a commercial planning system. Dose calculations on vCT and scatter corrected CBCT (CBCT) were compared by means of the proton range and a gamma-index analysis. For the H&N cases, an additional diagnostic replanning CT (rpCT) acquired within three days of the CBCT served as additional reference. For the prostate patients, a comprehensive contour comparison of CBCT and vCT, using a trained physician's delineation, was performed.

Results: A high agreement of vCT and CBCT was found in terms of the proton range and gamma-index analysis. For all patients and indications between 95% and 100% of the proton dose profiles in beam's eye view showed a range agreement of better than 3 mm. The pass rate in a (2%,2 mm) gamma-comparison was between 96% and 100%. For H&N patients, an equivalent agreement of vCT and CBCT to the reference rpCT was observed. However, for the prostate cases, an insufficient accuracy of the vCT contours retrieved from DIR was found, while the CBCT contours showed very high agreement to the contours delineated on the raw CBCT.

Conclusions: For H&N patients, no considerable differences of vCT and CBCT were found. For prostate cases, despite the high dosimetric agreement, the DIR yields incorrect contours, probably due to the more pronounced anatomical changes in the abdomen and the reduced soft-tissue contrast in the CBCT. Using the vCT as prior, these inaccuracies can be overcome and images suitable for accurate delineation and dose calculation in CBCT-based adaptive IMPT can be retrieved from scatter correction of the CBCT projections.
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http://dx.doi.org/10.1118/1.4962933DOI Listing
October 2016

Motion-aware temporal regularization for improved 4D cone-beam computed tomography.

Phys Med Biol 2016 09 2;61(18):6856-6877. Epub 2016 Sep 2.

iMagX Project, ICTEAM Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium. Université de Lyon, CREATIS; CNRS UMR5220; Inserm U1044; INSA-Lyon; Université Lyon 1; Centre Léon Bérard, France.

Four-dimensional cone-beam computed tomography (4D-CBCT) of the free-breathing thorax is a valuable tool in image-guided radiation therapy of the thorax and the upper abdomen. It allows the determination of the position of a tumor throughout the breathing cycle, while only its mean position can be extracted from three-dimensional CBCT. The classical approaches are not fully satisfactory: respiration-correlated methods allow one to accurately locate high-contrast structures in any frame, but contain strong streak artifacts unless the acquisition is significantly slowed down. Motion-compensated methods can yield streak-free, but static, reconstructions. This work proposes a 4D-CBCT method that can be seen as a trade-off between respiration-correlated and motion-compensated reconstruction. It builds upon the existing reconstruction using spatial and temporal regularization (ROOSTER) and is called motion-aware ROOSTER (MA-ROOSTER). It performs temporal regularization along curved trajectories, following the motion estimated on a prior 4D CT scan. MA-ROOSTER does not involve motion-compensated forward and back projections: the input motion is used only during temporal regularization. MA-ROOSTER is compared to ROOSTER, motion-compensated Feldkamp-Davis-Kress (MC-FDK), and two respiration-correlated methods, on CBCT acquisitions of one physical phantom and two patients. It yields streak-free reconstructions, visually similar to MC-FDK, and robust information on tumor location throughout the breathing cycle. MA-ROOSTER also allows a variation of the lung tissue density during the breathing cycle, similar to that of planning CT, which is required for quantitative post-processing.
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http://dx.doi.org/10.1088/0031-9155/61/18/6856DOI Listing
September 2016

Technical Note: Procedure for the calibration and validation of kilo-voltage cone-beam CT models.

Med Phys 2016 Sep;43(9):5199

Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1206, INSA-Lyon, Université Lyon 1, Centre Léon Bérard, Lyon 69373 Cedex 08, France.

Purpose: The aim of this work is to propose a general and simple procedure for the calibration and validation of kilo-voltage cone-beam CT (kV CBCT) models against experimental data.

Methods: The calibration and validation of the CT model is a two-step procedure: the source model then the detector model. The source is described by the direction dependent photon energy spectrum at each voltage while the detector is described by the pixel intensity value as a function of the direction and the energy of incident photons. The measurements for the source consist of a series of dose measurements in air performed at each voltage with varying filter thicknesses and materials in front of the x-ray tube. The measurements for the detector are acquisitions of projection images using the same filters and several tube voltages. The proposed procedure has been applied to calibrate and assess the accuracy of simple models of the source and the detector of three commercial kV CBCT units. If the CBCT system models had been calibrated differently, the current procedure would have been exclusively used to validate the models. Several high-purity attenuation filters of aluminum, copper, and silver combined with a dosimeter which is sensitive to the range of voltages of interest were used. A sensitivity analysis of the model has also been conducted for each parameter of the source and the detector models.

Results: Average deviations between experimental and theoretical dose values are below 1.5% after calibration for the three x-ray sources. The predicted energy deposited in the detector agrees with experimental data within 4% for all imaging systems.

Conclusions: The authors developed and applied an experimental procedure to calibrate and validate any model of the source and the detector of a CBCT unit. The present protocol has been successfully applied to three x-ray imaging systems. The minimum requirements in terms of material and equipment would make its implementation suitable in most clinical environments.
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http://dx.doi.org/10.1118/1.4961400DOI Listing
September 2016

Fast reconstruction of low dose proton CT by sinogram interpolation.

Phys Med Biol 2016 08 22;61(15):5868-82. Epub 2016 Jul 22.

Department of Oncology, Aarhus University Hospital, Nørrebrogade 44, building 5, DK-8000 Aarhus C, Denmark.

Proton computed tomography (CT) has been demonstrated as a promising image modality in particle therapy planning. It can reduce errors in particle range calculations and consequently improve dose calculations. Obtaining a high imaging resolution has traditionally required computationally expensive iterative reconstruction techniques to account for the multiple scattering of the protons. Recently, techniques for direct reconstruction have been developed, but these require a higher imaging dose than the iterative methods. No previous work has compared the image quality of the direct and the iterative methods. In this article, we extend the methodology for direct reconstruction to be applicable for low imaging doses and compare the obtained results with three state-of-the-art iterative algorithms. We find that the direct method yields comparable resolution and image quality to the iterative methods, even at 1 mSv dose levels, while yielding a twentyfold speedup in reconstruction time over previously published iterative algorithms.
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http://dx.doi.org/10.1088/0031-9155/61/15/5868DOI Listing
August 2016

Filtered-backprojection reconstruction for a cone-beam computed tomography scanner with independent source and detector rotations.

Med Phys 2016 May;43(5):2344

Institute for Research and Development on Advanced Radiation Technologies (radART), Paracelsus Medical University, Strubergasse 16, Salzburg 5020, Austria and medPhoton GmbH, Strubergasse 16, Salzburg 5020, Austria.

Purpose: A new cone-beam CT scanner for image-guided radiotherapy (IGRT) can independently rotate the source and the detector along circular trajectories. Existing reconstruction algorithms are not suitable for this scanning geometry. The authors propose and evaluate a three-dimensional (3D) filtered-backprojection reconstruction for this situation.

Methods: The source and the detector trajectories are tuned to image a field-of-view (FOV) that is offset with respect to the center-of-rotation. The new reconstruction formula is derived from the Feldkamp algorithm and results in a similar three-step algorithm: projection weighting, ramp filtering, and weighted backprojection. Simulations of a Shepp Logan digital phantom were used to evaluate the new algorithm with a 10 cm-offset FOV. A real cone-beam CT image with an 8.5 cm-offset FOV was also obtained from projections of an anthropomorphic head phantom.

Results: The quality of the cone-beam CT images reconstructed using the new algorithm was similar to those using the Feldkamp algorithm which is used in conventional cone-beam CT. The real image of the head phantom exhibited comparable image quality to that of existing systems.

Conclusions: The authors have proposed a 3D filtered-backprojection reconstruction for scanners with independent source and detector rotations that is practical and effective. This algorithm forms the basis for exploiting the scanner's unique capabilities in IGRT protocols.
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http://dx.doi.org/10.1118/1.4945418DOI Listing
May 2016

Evaluation of a new transperineal ultrasound probe for inter-fraction image-guidance for definitive and post-operative prostate cancer radiotherapy.

Phys Med 2016 Mar 2;32(3):499-505. Epub 2016 Feb 2.

CREATIS, INSA, Université de Lyon, CNRS UMR5220, Inserm U1044, Lyon F-69622, France; Léon Bérard Cancer Center, University of Lyon, Lyon F-69373, France. Electronic address:

Purpose: The aim of this study was to evaluate a new system based on transperineal ultrasound (TP-US) acquisitions for prostate and post-prostatectomy pre-treatment positioning by comparing this device to cone-beam computed tomography (CBCT).

Methods: The differences between CBCT/CT and TP-US/TP-US registrations were analyzed on 427 and 453 sessions for 13 prostate and 14 post-prostatectomy patients, respectively. The inter-operator variability (IOV) of the registration process, and the impact and variability of the probe pressure were also evaluated.

Results: CBCT and TP-US shift agreements at ± 5 mm were 76.6%, 95.1%, 96.3% and 90.3%, 85.0%, 97.6% in anterior-posterior, superior-inferior and left-right directions, for prostate and post-prostatectomy patients, respectively. IOV values were similar between the 2 modalities. Displacements above 5 mm due to strong pressures were observed on both localizations, but such pressures were rarely reproduced during treatment courses.

Conclusions: High concordance between CBCT/CT and TP-US/TP-US localization of prostates or prostatic beds was found in this study. TP-US based prepositioning is a feasible method to ensure accurate treatment delivery, and represents an attractive alternative to invasive and/or irradiating imaging modalities.
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http://dx.doi.org/10.1016/j.ejmp.2016.01.481DOI Listing
March 2016

Development of 2D+T tracking algorithm in ultrasound images for radiotherapy.

Annu Int Conf IEEE Eng Med Biol Soc 2015 Aug;2015:2916-9

The aim of this study is to develop and validate a deformable tracking algorithm for monitoring the motion of the target volume on 2D ultrasound (US) images during a radiotherapy fraction. The proposed method is applied on images acquired with a transperineal ultrasound (TP-US) probe on 31 treatment patient's sessions, treated with a prostate or after a surgery, called a prostatectomy. The developed algorithm is based on Speeded-Up Robust Features (SURF) to find and match the corresponding salient points in the reference and moving images, and Thin Plate Spline (TPS) to warp the image. The results are promising and show that the proposed algorithm performs well with either artificial transforms, or in comparison with a rigid intensity based algorithm used in clinic.
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http://dx.doi.org/10.1109/EMBC.2015.7319002DOI Listing
August 2015

Ultrasound versus Cone-beam CT image-guided radiotherapy for prostate and post-prostatectomy pretreatment localization.

Phys Med 2015 Dec 28;31(8):997-1004. Epub 2015 Sep 28.

CREATIS, Université de Lyon, Lyon, France; CNRS UMR5220, Lyon, France; Inserm U1044, Lyon, France; INSA-Lyon, Lyon, France; Université Lyon 1, Lyon, France; Centre Léon Bérard, Lyon, France. Electronic address:

Purpose: To evaluate the accuracy of an intra-modality trans-abdominal ultrasound (TA-US) device against soft-tissue based Cone-Beam Computed tomography (CBCT) registration for prostate and post-prostatectomy pre-treatment positioning.

Methods: The differences between CBCT and US shifts were calculated on 25 prostate cancer patients (cohort A) and 11 post-prostatectomy patients (cohort B), resulting in 284 and 106 paired shifts for cohorts A and B, respectively. As a second step, a corrective method was applied to the US registration results to decrease the systematic shifts observed between TA-US and CBCT results. This method consisted of subtracting the mean difference obtained between US and CBCT registration results during the first 3 sessions from the US registration results of the subsequent sessions. Inter-operator registration variability (IOV) was also investigated for both modalities.

Results: After initial review, about 20% of the US images were excluded because of insufficient quality. The average differences between US and CBCT were: 2.8 ± 4.1 mm, -0.9 ± 4.2 mm, 0.4 ± 3.4 mm for cohort A and 1.3 ± 5.0 mm, -2.3 ± 4.6 mm, 0.5 ± 2.9 mm for cohort B, in the anterior-posterior (AP), superior-inferior (SI) and lateral (LR) directions, respectively. After applying the corrective method, only the differences in the AP direction remained significant (p < 0.05). The IOV values were between 0.6-2.0 mm and 2.1-3.5 mm for the CBCT and TA-US modalities, respectively.

Conclusions: Based on the obtained results and on the image quality, the TA-US imaging modality is not safely interchangeable with CBCT for pre-treatment repositioning. Treatment margins adaptation based on the correction of the systematic shifts should be considered.
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http://dx.doi.org/10.1016/j.ejmp.2015.07.147DOI Listing
December 2015

Dose fractionation in synchrotron radiation x-ray phase micro-tomography.

Phys Med Biol 2015 Oct 15;60(19):7543-66. Epub 2015 Sep 15.

European Synchrotron Radiation Facility, 6 rue Jules Horowitz, F-38043 Grenoble Cedex, France. Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, 7 avenue Jean Capelle, F-69621 Villeurbanne, France. Currently at Université de Grenoble Alpes, LMGP, CNRS UMR5628, Grenoble Institute of Technology, MINATEC, 3 parvis Louis Néel, 38016 Grenoble Grenoble, France. EVEON SAS, 345 rue Lavoisier, Inovallée, F-38330 Montbonnot Saint-Martin, France.

Phase sensitive x-ray imaging expands the applicability of standard attenuation based techniques by offering several orders of magnitude of increase in sensitivity. Due to the short wavelength, x-ray phase is not directly measurable, but has to be put in evidence by the use of phase contrast techniques. The phase can then be reconstructed from one or several phase contrast images. In this study, we consider synchrotron x-ray phase micro-computed tomography (μCT) based on free space propagation for heterogeneous and strongly absorbing objects. This technique generally relies on acquiring several scans of the sample at different detector distances. It is also generally believed that multi-distance phase μCT needs a higher dose input than single distance phase μCT. The purpose of this work is to study the impact of different means of dose fractionation on the reconstructed image quality. We define different acquistion schemes in multi-distance in-line phase μCT. Previously, the exposure time at each sample-to-detector distance was usually kept the same. Here, we let not only the number of distances vary but also the fraction of exposure time at each distance, the total exposure time being kept constant. Phase retrieval is performed with the mixed approach algorithm. The reconstructed μCT images are compared in terms of accuracy, precision and resolution. In addition, we also compare the result of dose fractionated multi distance phase μCT to single distance phase μCT using the same total radiation dose. In the multi-distance approach, we find that using different exposure times on each distance improves the image quality in the reconstructed image. Further, we show that, despite having the same total dose delivery, the multi distance imaging method gives better image quality than the single distance method, at the cost of an additional overhead from camera displacements and reference images. We show that by optimizing the acquistion parameters in terms of number of distances and exposure time at each distance, the resulting image quality can be improved. This means that for a desired image quality, a lower radiation dose can be used. This is important especially in high resolution imaging where the radiation dose used for imaging can be very large, potentially damaging the sample. Based on the acquired data, we define an optimal protocol for use in together with the heterogeneous object mixed approach.
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http://dx.doi.org/10.1088/0031-9155/60/19/7543DOI Listing
October 2015

Semiautomatic registration of 3D transabdominal ultrasound images for patient repositioning during postprostatectomy radiotherapy.

Med Phys 2014 Dec;41(12):122903

Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Lyon F-69621, France and Léon Bérard Cancer Center, Université de Lyon, Lyon F-69373, France.

Purpose: The aim of the present work is to propose and evaluate registration algorithms of three-dimensional (3D) transabdominal (TA) ultrasound (US) images to setup postprostatectomy patients during radiation therapy.

Methods: Three registration methods have been developed and evaluated to register a reference 3D-TA-US image acquired during the planning CT session and a 3D-TA-US image acquired before each treatment session. The first method (method A) uses only gray value information, whereas the second one (method B) uses only gradient information. The third one (method C) combines both sets of information. All methods restrict the comparison to a region of interest computed from the dilated reference positioning volume drawn on the reference image and use mutual information as a similarity measure. The considered geometric transformations are translations and have been optimized by using the adaptive stochastic gradient descent algorithm. Validation has been carried out using manual registration by three operators of the same set of image pairs as the algorithms. Sixty-two treatment US images of seven patients irradiated after a prostatectomy have been registered to their corresponding reference US image. The reference registration has been defined as the average of the manual registration values. Registration error has been calculated by subtracting the reference registration from the algorithm result. For each session, the method has been considered a failure if the registration error was above both the interoperator variability of the session and a global threshold of 3.0 mm.

Results: All proposed registration algorithms have no systematic bias. Method B leads to the best results with mean errors of -0.6, 0.7, and -0.2 mm in left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions, respectively. With this method, the standard deviations of the mean error are of 1.7, 2.4, and 2.6 mm in LR, SI, and AP directions, respectively. The latter are inferior to the interoperator registration variabilities which are of 2.5, 2.5, and 3.5 mm in LR, SI, and AP directions, respectively. Failures occur in 5%, 18%, and 10% of cases in LR, SI, and AP directions, respectively. 69% of the sessions have no failure.

Conclusions: Results of the best proposed registration algorithm of 3D-TA-US images for postprostatectomy treatment have no bias and are in the same variability range as manual registration. As the algorithm requires a short computation time, it could be used in clinical practice provided that a visual review is performed.
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http://dx.doi.org/10.1118/1.4901642DOI Listing
December 2014

Learning directional relative positions between mediastinal lymph node stations and organs.

Med Phys 2014 Jun;41(6):061905

Department of Radiation Oncology, Andrew Love Cancer Centre, Barwon Health, Geelong 3220, Australia.

Purpose: To automatically learn directional relative positions (DRP) between mediastinal lymph node stations and anatomical organs. Those spatial relationships are used to semiautomatically segment the stations in thoracic CT images.

Methods: Fuzzy maps of DRP were automatically extracted by a learning procedure from a database composed of images with stations and anatomical structures manually segmented by consensus between experts. Spatial relationships common to all patients were retained. The segmentation of a new image used an initial rough delineation of anatomical organs and applied the DRP operators. The algorithm was tested with a leave-one-out approach on a database of 5 patients with 10 lymph stations and 30 anatomical structures each. Results were compared to expert delineations with dice similarity coefficient (DSC) and bidirectional local distance (BLD).

Results: The overall mean DSC was 66% and the mean BLD was 1.7 mm. Best matches were obtained from stations S3P or S4R while lower matches were obtained for stations 1R and 1L. On average, more than 30 spatial relationships were automatically extracted for each station.

Conclusions: This feasibility study suggests that mediastinal lymph node stations could be satisfactory segmented from thoracic CT using automatically extracted positional relationships with anatomical organs. This approach requires the anatomical structures to be initially roughly delineated. A similar approach could be applied to other sites where spatial relationships exists between anatomical structures. The complete database of the five reference cases is made publicly available.
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http://dx.doi.org/10.1118/1.4873677DOI Listing
June 2014
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