Matthieu Bal

Metal artifact reduction in CT using tissue-class modeling and adaptive prefiltering.

High-density objects such as metal prostheses, surgical clips, or dental fillings generate streak-like artifacts in computed tomography images. We present a novel method for metal artifact reduction by in-painting missing information into the corrupted sinogram. The information is provided by a tissue-class model extracted from the distorted image. To this end the image is first adaptively filtered to reduce the noise content and to smooth out streak artifacts. Consecutively, the image is segmented into different material classes using a clustering algorithm. The corrupted and missing information in the original sinogram is completed using the forward projected information from the tissue-class model. The performance of the correction method is assessed on phantom images. Clinical images featuring a broad spectrum of metal artifacts are studied. Phantom and clinical studies show that metal artifacts, such as streaks, are significantly reduced and shadows in the image are eliminated. Furthermore, the novel approach improves detectability of organ contours. This can be of great relevance, for instance, in radiation therapy planning, where images affected by metal artifacts may lead to suboptimal treatment plans.

Evaluation of a compartmental model for estimating tumor hypoxia via FMISO dynamic PET imaging.

This paper systematically evaluates a pharmacokinetic compartmental model for identifying tumor hypoxia using dynamic positron emission tomography (PET) imaging with 18F-fluoromisonidazole (FMISO). A generic irreversible one-plasma two-tissue compartmental model was used. A dynamic PET image dataset was simulated with three tumor regions-normoxic, hypoxic and necrotic-embedded in a normal-tissue background, and with an image-based arterial input function. Each voxelized tissues time activity curve (TAC) was simulated with typical values of kinetic parameters, as deduced from FMISO-PET data from nine head-and-neck cancer patients. The dynamic dataset was first produced without any statistical noise to ensure that correct kinetic parameters were reproducible. Next, to investigate the stability of kinetic parameter estimation in the presence of noise, 1000 noisy samples of the dynamic dataset were generated, from which 1000 noisy estimates of kinetic parameters were calculated and used to estimate the sample mean and covariance matrix. It is found that a more peaked input function gave less variation in various kinetic parameters, and the variation of kinetic parameters could also be reduced by two region-of-interest averaging techniques. To further investigate how bias in the arterial input function affected the kinetic parameter estimation, a shift error was introduced in the peak amplitude and peak location of the input TAC, and the bias of various kinetic parameters calculated. In summary, mathematical phantom studies have been used to determine the statistical accuracy and precision of model-based kinetic analysis, which helps to validate this analysis and provides guidance in planning clinical dynamic FMISO-PET studies.

High precision bladder cancer irradiation by integrating a library planning procedure of 6 prospectively generated SIB IMRT plans with image guidance using lipiodol markers

PURPOSE To increase local control and decrease side effects for urinary bladder cancer patients by integrating a library planning procedure with image guidance using lipiodol markers. METHODS AND MATERIALS Twenty patients with T2-T4N0M0 grade 2-3 invasive bladder carcinoma were treated according to an online adaptive protocol. Initially, the gross tumour volume (GTV) was demarcated during cystoscopy by injecting several drops of lipiodol in the submucosa around the tumour. Subsequently two CT scans were acquired with a full bladder and a voided bladder. On both scans, the boost volume (GTV) and the low-risk bladder volume were delineated. Using an interpolation tool, six concomitant boost IMRT plans with increasing bladder volumes were generated. For each fraction the procedure at the treatment unit was as follows: Firstly, a ConeBeam-CT was acquired and based on the amount of bladder filling the best fitting bladder contours and corresponding GTV and IMRT plans were selected. Secondly, the lipiodol markers were registered using the corresponding GTV contours and it was verified that the corresponding 95%-isodose surface covered the entire bladder. Finally, an online setup correction was applied based on this registration and the corresponding treatment plan was irradiated. RESULTS The lipiodol markers were very useful in outlining the GTV at the planning CT and for daily setup correction. While the patients strived for a full bladder filling at time of the treatment, this was seldom accomplished. Due to our protocol an appropriate plan with adequate coverage of the PTV and without excessive dose to healthy tissue was delivered every day. The treatment was very well tolerated by all patients. At the end of the treatment no grade 3 urinary or gastro-intestinal toxicity was observed. After a median follow-up of 28 months two local relapses occurred. CONCLUSION Using the library planning approach combined with online image guidance using lipiodol markers, we were able to deliver a highly conformal dose distribution to all bladder cancer patients achieving promising clinical results.

Dose painting by contours versus dose painting by numbers for stage II/III lung cancer: Practical implications of using a broad or sharp brush

PURPOSE Local recurrence rates are high in patients with locally advanced NSCLC treated with 60 to 66 Gy in 2 Gy fractions. It is hypothesised that boosting volumes with high SUV on the pre-treatment FDG-PET scan potentially increases local control while maintaining acceptable toxicity levels. We compared two approaches: threshold-based dose painting by contours (DPBC) with voxel-based dose painting by numbers (DPBN). MATERIALS AND METHODS Two dose painted plans were generated for 10 stage II/III NSCLC patients with 66 Gy at 2-Gy fractions to the entire PTV and a boost dose to the high SUV areas within the primary GTV. DPBC aims for a uniform boost dose at the volume encompassing the SUV 50%-region (GTV(boost)). DPBN aims for a linear relationship between the boost dose to a voxel and the underlying SUV. For both approaches the boost dose was escalated up to 130 Gy (in 33 fractions) or until the dose limiting constraint of an organ at risk was met. RESULTS For three patients (with relatively small peripheral tumours) the dose within the GTV could be boosted to 130 Gy using both strategies. For the remaining patients the boost dose was confined by a critical structure (mediastinal structures in six patients, lungs in one patient). In general the amount of large brush DPBC boosting is limited whenever the GTV(boost) is close to any serial risk organ. In contrast, small brush DPBN inherently boosts at a voxel-by-voxel basis allowing significant higher dose values to high SUV voxels more distant from the organs at risk. We found that the biological SUV gradients are reasonably congruent with the dose gradients that standard linear accelerators can deliver. CONCLUSIONS Both large brush DPBC and sharp brush DPBN techniques can be used to considerably boost the dose to the FDG avid regions. However, significantly higher boost levels can be obtained using sharp brush DPBN although sometimes at the cost of a less increased dose to the low SUV regions.

The first patient treatment of computed tomography ventilation functional image-guided radiotherapy for lung cancer.

BACKGROUND AND PURPOSE Radiotherapy that selectively avoids irradiating highly-functional lung regions may reduce pulmonary toxicity. We report on the first clinical implementation and patient treatment of lung functional image-guided radiotherapy using an emerging technology, computed tomography (CT) ventilation imaging. MATERIAL AND METHODS A protocol was developed to investigate the safety and feasibility of CT ventilation functional image-guided radiotherapy. CT ventilation imaging is based on (1) deformable image registration of four-dimensional (4D) CT images, and (2) quantitative image analysis for regional volume change, a surrogate for ventilation. CT ventilation functional image-guided radiotherapy plans were designed to minimize specific lung dose-function metrics, including functional V20 (fV20), while maintaining target coverage and meeting standard constraints to other critical organs. RESULTS CT ventilation functional image-guided treatment planning reduced the lung fV20 by 5% compared to an anatomic image-guided plan for an enrolled patient with stage IIIB non-small cell lung cancer. Although the doses to several other critical organs increased, the necessary constraints were all met. CONCLUSIONS An emerging technology, CT ventilation imaging has been translated into the clinic and used in functional image-guided radiotherapy for the first time. This milestone represents an important first step toward hypothetically reduced pulmonary toxicity in lung cancer radiotherapy.

CT ventilation functional image-based IMRT treatment plans are comparable to SPECT ventilation functional image-based plans

PURPOSE To investigate the hypothesis that CT ventilation functional image-based IMRT plans designed to avoid irradiating highly-functional lung regions are comparable to single-photon emission CT (SPECT) ventilation functional image-based plans. METHODS AND MATERIALS Three IMRT plans were created for eight thoracic cancer patients using: (1) CT ventilation functional images, (2) SPECT ventilation functional images, and (3) anatomic images (no functional images). CT ventilation images were created by deformable image registration of 4D-CT image data sets and quantitative analysis. The resulting plans were analyzed for the relationship between the deviations of CT-functional plan metrics from anatomic plan metrics (ΔCT-anatomic) and those of SPECT-functional plans (ΔSPECT-anatomic), and moreover for agreements of various metrics between the CT-functional and SPECT-functional plans. RESULTS The relationship between ΔCT-anatomic and ΔSPECT-anatomic was strong (e.g., R=0.94; linear regression slope 0.71). The average differences and 95% limits of agreement between the CT-functional and SPECT-functional plan metrics (except for monitor units) for various structures were mostly less than 1% and 2%, respectively. CONCLUSIONS This study demonstrated a reasonable agreement between the CT ventilation functional image-based IMRT plans and SPECT-functional plans, suggesting the potential for CT ventilation imaging to serve as a surrogate for SPECT ventilation in functional image-guided radiotherapy.

A radial adaptive filter for metal artifact reduction

High-density objects, such as metal prostheses or surgical clips, generate streak-like artifacts in CT images. We designed a radial adaptive filter, which directly operates on the corrupted reconstructed image, to effectively and efficiently reduce such artifacts. The filter adapts to the severity of local artifacts to preserve spatial resolution as much as possible. The widths and direction of the filter are derived from the local structure tensor. Visual inspection shows that this novel radial adaptive filter is superior with respect to existing methods in the case of mildly distorted images. In the presence of strong artifacts we propose a hybrid approach. An image corrected with a standard method, which performs well on images with regions of severe artifacts, is fused with an adaptively filtered clone to combine the strengths of both methods.

Probabilistic treatment planning for pancreatic cancer treatment: prospective incorporation of respiratory motion shows only limited dosimetric benefit

Abstract Background: We introduced a probabilistic treatment planning approach that prospectively incorporates respiratory-induced motion in the treatment plan optimization. The aim of this study was to determine the potential dosimetric benefit by comparing this approach to the use of an internal target volume (ITV). Material and method: We retrospectively compared the probabilistic respiratory motion-incorporated (RMI) approach to the ITV approach for 18 pancreatic cancer patients, for seven simulated respiratory amplitudes from 5 to 50 mm in the superior-inferior (SI) direction. For each plan, we assessed the target coverage (required: D98%≥95% of 50 Gy prescribed dose). For the RMI plans, we investigated whether target coverage was robust against daily variations in respiratory amplitude. We determined the distance between the clinical target volume and the 30 Gy isodose line (i.e. dose gradient steepness) in the SI direction. To investigate the clinical benefit of the RMI approach, we created for each patient an ITV and RMI treatment plan for the three-dimensional (3D) respiratory amplitudes observed on their pretreatment 4D computed tomography (4DCT). We determined Dmean, V30Gy, V40Gy and V50Gy for the duodenum. Results: All treatment plans yielded good target coverage. The RMI plans were robust against respiratory amplitude variations up to 10 mm, as D98% remained ≥95%. We observed steeper dose gradients compared to the ITV approach, with a mean decrease from 25.9 to 19.2 mm for a motion amplitude of 50 mm. For the 4DCT motion amplitudes, the RMI approach resulted in a mean decrease of 0.43 Gy, 1.1 cm3, 1.4 cm3 and 0.9 cm3 for the Dmean, V30Gy, V40Gy and V50Gy of the duodenum, respectively. Conclusion: The probabilistic treatment planning approach yielded significantly steeper dose gradients and therefore significantly lower dose to surrounding healthy tissues than the ITV approach. However, the observed dosimetric gain for clinically observed respiratory motion amplitudes for this patient group was limited.

TH‐E‐BRF‐02: 4D‐CT Ventilation Image‐Based IMRT Plans Are Dosimetrically Comparable to SPECT Ventilation Image‐Based Plans

PURPOSE An emerging lung ventilation imaging method based on 4D-CT can be used in radiotherapy to selectively avoid irradiating highly-functional lung regions, which may reduce pulmonary toxicity. Efforts to validate 4DCT ventilation imaging have been focused on comparison with other imaging modalities including SPECT and xenon CT. The purpose of this study was to compare 4D-CT ventilation image-based functional IMRT plans with SPECT ventilation image-based plans as reference. METHODS 4D-CT and SPECT ventilation scans were acquired for five thoracic cancer patients in an IRB-approved prospective clinical trial. The ventilation images were created by quantitative analysis of regional volume changes (a surrogate for ventilation) using deformable image registration of the 4D-CT images. A pair of 4D-CT ventilation and SPECT ventilation image-based IMRT plans was created for each patient. Regional ventilation information was incorporated into lung dose-volume objectives for IMRT optimization by assigning different weights on a voxel-by-voxel basis. The objectives and constraints of the other structures in the plan were kept identical. The differences in the dose-volume metrics have been evaluated and tested by a paired t-test. SPECT ventilation was used to calculate the lung functional dose-volume metrics (i.e., mean dose, V20 and effective dose) for both 4D-CT ventilation image-based and SPECT ventilation image-based plans. RESULTS Overall there were no statistically significant differences in any dose-volume metrics between the 4D-CT and SPECT ventilation imagebased plans. For example, the average functional mean lung dose of the 4D-CT plans was 26.1±9.15 (Gy), which was comparable to 25.2±8.60 (Gy) of the SPECT plans (p = 0.89). For other critical organs and PTV, nonsignificant differences were found as well. CONCLUSION This study has demonstrated that 4D-CT ventilation image-based functional IMRT plans are dosimetrically comparable to SPECT ventilation image-based plans, providing evidence to use 4D-CT ventilation imaging for clinical applications. Supported in part by Free to Breathe Young Investigator Research Grant and NIH/NCI R01 CA 093626. The authors thank Philips Radiation Oncology Systems for the Pinnacle3 treatment planning systems.

SU‐GG‐J‐02: Dose Painting by Numbers Based on SUV Data for Advanced Lung Tumors

Purpose: to develop a plugin with user interface for the Pinnacle TPS (Philips Medical Systems) to directly integrate SUV data obtained by PET‐scanning into the optimization process for lungtumorIMRT plans. Method and Materials: A plugin generating a grid with the prescribed dose per voxel was developed. The prescribed dose values are based on the underlying SUV data per voxel, not on contours. Various user‐defined functions can be used to give the relation between SUV data and prescribed dose. New objective functions were generated to calculate a cost based on the voxel‐by‐voxel difference between the actual dose distribution and the prescribed dose distribution. During the IMRT optimization these (biological) objective functions are used in conjunction with conventional dose volume objectives process. Further tools were developed to create a SUV‐Volume Histogram, showing the SUV distribution in any ROI, and to visualize the quality of the resulting plan by showing the distribution of the voxel‐by‐voxel differences between prescribed and actual dose distribution. Results: With the plugin SUV‐based dose prescriptions were made. After optimization with the plugin, which took only several minutes per plan, plans were evaluated with the newly devised tools. Optimization resulted in doses to regions with high SUV of typically 130% – 200% of the current clinical dose. Mean lung dose and other dose objectives, which were unaltered from standard IMRT optimization, were met for all plans. Conclusion: A plugin was developed enabling us to steer the dose within the lung GTV based on the underlying SUV distribution. Using these tools we were able to boost voxels with high SUV up to a dose level of up to 200% of the current clinical dose with only very limited dose increase to the normal structures as lung and spine. Conflict of Interest: Research sponsored by Philips Medical Systems