Evaluation and commissioning of a surface based system for respiratory sensing in 4D CT

Spadea, Maria Francesca; Baroni, Guido; Gierga, David P.; Turcotte, J; Chen, George T.Y.; Sharp, G

doi:10.1120/jacmp.v12i1.3288

Cited by 24 publications

(28 citation statements)

References 10 publications

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“…The pressure sensor studied by Otani et al involves a small pressure sensor inserted into the pocket of a belt, which was not the same pneumatic system studied in this work. Spadea et al (24) and Kauweloa et al (25) explored the differences between using surface imaging cameras (GateCT, VisionRT Ltd., London, UK) to track the patient's abdomen as an external surrogate with Varian's RPM system in a variety of 4D CT phantom experiments. Like our study, both investigators obtained near‐perfect correlations between GateCT and RPM with phantom measurements.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of two synchronized external surrogates for 4D CT sorting

Glide-Hurst

Smith

Ajlouni

et al. 2013

J Applied Clin Med Phys

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The purpose of this study was to quantify the performance and agreement between two different external surrogate acquisition systems: Varian's Real‐Time Position Management (RPM) and Philips Medical Systems' pneumatic bellows, in the context of waveform and 4D CT image analysis. Eight patient displacement curves derived from RPM data were inputted into a motion platform with varying amplitudes (0.5 to 3 cm) and patterns. Simultaneous 4D CT acquisition, with synchronized X‐ray on detection, was performed with the bellows and RPM block placed on the platform. Bellows data were used for online retrospective phase‐based sorting, while RPM data were used for off‐line reconstruction of raw 4D CT data. RPM and bellows breathing curves were resampled, normalized, and analyzed to determine associations between different external surrogates, relative amplitude differences, and system latency. Maximum intensity projection (MIP) images were generated, phantom targets were delineated, and volume differences, overlap index, and Dice similarity coefficient differences were evaluated. A prospective patient study of ten patients was performed and waveforms were evaluated for latency (i.e., absolute time differences) and overall agreement. 4D CT sorting quality and subtraction images were assessed. Near perfect associations between the RPM and bellows‐acquired breathing traces were found false(Pearson′normals.25emr=0.987−0.999false). Target volumes were 200.4±12.25emcc.25emand.25em199.8±12.6.25emcc for RPM and bellows targets, respectively, which was not significantly different false(normalU=33,.25emp>0.05false). Negligible centroid variations were observed between bellows and RPM‐contoured MIP targets (largest discrepancy=−0.24±0.31.25emmm in superior‐inferior direction). The maximum volume difference was observed for an RPM target 2.5 cc (1%) less than bellows, yielding the largest difference in centroid displacement (0.9 mm). Strong correlations in bellows and RPM waveforms were observed for all patients false(0.947±0.037false). Latency between external surrogates was <100.25emms for phantom and patient data. Negligible differences were observed between MIP, end‐exhale, and end‐inhale phase images for all cases, with delineated RPM and bellows lung volumes demonstrating a mean difference of −0.3±0.51%. Dice similarity coefficients and overlap indices were near unity for phantom target volumes and patient lung volumes. Slight differences were observed in waveform and latency analysis between Philips bellows and Varian's RPM, although these did not translate to differences in image quality or impact delineations. Therefore, the two systems were found to be equivalent external surrogates in the context of 4D CT for treatment planning purposes.PACS numbers: 87.57.Q‐, 07.07.Df

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Section: Discussionmentioning

confidence: 99%

Evaluation of two synchronized external surrogates for 4D CT sorting

Glide-Hurst

Smith

Ajlouni

et al. 2013

J Applied Clin Med Phys

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“…In addition, different recent studies have proposed the use of external patient surface information for respiratory motion synchronization in 4D CT imaging. [20][21][22] Therefore, the main objective of this study was to demonstrate the interest of using the motion of a patient's entire surface in comparison with the use of 1D respiratory signals for the construction of a patient's specific respiratory motion model. The 3D surfaces used here are extracted by segmenting 4D CT series for each patient, although in practical terms 3D patient surface measurements can be also provided by systems such as, for example, a time of flight (ToF) camera 23 which actively illuminates a patient with an incoherent light signal.…”

Section: Introductionmentioning

confidence: 99%

Patient specific respiratory motion modeling using a 3D patient's external surface

et al. 2012

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Purpose: Respiratory motion modeling of both tumor and surrounding tissues is a key element in minimizing errors and uncertainties in radiation therapy. Different continuous motion models have been previously developed. However, most of these models are based on the use of parameters such as amplitude and phase extracted from 1D external respiratory signal. A potentially reduced correlation between the internal structures (tumor and healthy organs) and the corresponding external surrogates obtained from such 1D respiratory signal is a limitation of these models. The objective of this work is to describe a continuous patient specific respiratory motion model, accounting for the irregular nature of respiratory signals, using patient external surface information as surrogate measures rather than a 1D respiratory signal. Methods: Ten patients were used in this study having each one 4D CT series, a synchronized RPM signal and patient surfaces extracted from the 4D CT volumes using a threshold based segmentation algorithm. A patient specific model based on the use of principal component analysis was subsequently constructed. This model relates the internal motion described by deformation matrices and the external motion characterized by the amplitude and the phase of the respiratory signal in the case of the RPM or using specific regions of interest (ROI) in the case of the patients' external surface utilization. The capability of the different models considered to handle the irregular nature of respiration was assessed using two repeated 4D CT acquisitions (in two patients) and static CT images acquired at extreme respiration conditions (end of inspiration and expiration) for one patient. Results: Both quantitative and qualitative parameters covering local and global measures, including an expert observer study, were used to assess and compare the performance of the different motion estimation models considered. Results indicate that using surface information [correlation coefficient (CC): 0.998 6 0.0006 and model error (ME): 1.35 6 0.21 mm] is superior to the use of both motion phase and amplitude extracted from a 1D respiratory signal (CC and ME of 0.971 6 0.02 and 1.64 6 0.28 mm). The difference in performance was more substantial compared to the use of only one parameter (phase or amplitude) used in the motion model construction. Similarly, the patient surface based model was better in estimating the motion in the repeated 4D CT acquisitions and those CT images acquired at the full inspiration (FI) and the full expiration (FE). Once more, within this context the use of both amplitude and phase in the model building was substantially more robust than the use of phase or amplitude only. Conclusions: The present study demonstrates the potential of using external patient surfaces for the construction of patient specific respiratory motion models. Such information can be obtained using different devices currently available. The use of external surface information led to the best performance in estimating internal stru...

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“…After the testing the assembly phase will follow and the first full setup will be ready to be installed in medical facilities, presumably in 2 years. Once ready, thanks to its ability to detect and distinguish different types of radiation and its specific design, the pCT scanner can be employed not solely for proton imaging but also for additional online applications during the treatment allowing motion tracking during respiration, complementing other X-ray or surfaced based methods [67]. Given the lack of the front tracker, the detector could be positioned downstream of the patient during the treatment with a carbon-helium mixed beam, where carbon ions would be used for treatment and helium ions would be used for verification [67].…”

Section: Discussionmentioning

confidence: 99%

A High-Granularity Digital Tracking Calorimeter Optimized for Proton CT

Alme¹,

Barnaföldi²,

Barthel³

et al. 2020

Front. Phys.

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A typical proton CT (pCT) detector comprises a tracking system, used to measure the proton position before and after the imaged object, and an energy/range detector to measure the residual proton range after crossing the object. The Bergen pCT collaboration was established to design and build a prototype pCT scanner with a high granularity digital tracking calorimeter used as both tracking and energy/range detector. In this work the conceptual design and the layout of the mechanical and electronics implementation, along with Monte Carlo simulations of the new pCT system are reported. The digital tracking calorimeter is a multilayer structure with a lateral aperture of 27 cm × 16.6 cm, made of 41 detector/absorber sandwich layers (calorimeter), with aluminum (3.5 mm) used both as absorber and carrier, and two additional layers used as tracking system (rear trackers) positioned downstream of the imaged object; no tracking upstream the object is included. The rear tracker's structure only differs from the calorimeter layers for the carrier made of ∼200 μm carbon fleece and carbon paper (carbon-epoxy sandwich), to minimize scattering. Each sensitive layer consists of 108 ALICE pixel detector (ALPIDE) chip sensors (developed for ALICE, CERN) bonded on a polyimide flex and subsequently bonded to a larger flexible printed circuit board. Beam tests tailored to the pCT operation have been performed using high-energetic (50-220 MeV/u) proton and ion beams at the

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Evaluation and commissioning of a surface based system for respiratory sensing in 4D CT

Cited by 24 publications

References 10 publications

Evaluation of two synchronized external surrogates for 4D CT sorting

Evaluation of two synchronized external surrogates for 4D CT sorting

Patient specific respiratory motion modeling using a 3D patient's external surface

A High-Granularity Digital Tracking Calorimeter Optimized for Proton CT

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