Prediction of image noise contributions in proton computed tomography and comparison to measurements

We present a method to accurately predict image noise in proton computed tomography (pCT) using data generated from a Monte Carlo simulation and a patient or object model that may be generated from a prior x-ray CT image. This enables noise prediction for arbitrary beam fluence settings and, therefore, the application of fluence-modulated pCT (FMpCT), which can achieve prescribed noise targets and may significantly reduce the integral patient dose. We extended an existing Monte Carlo simulation of a prototype pCT scanner to include effects of quenching in the energy detector scintillators and constructed a beam model from experimental tracking data. Simulated noise predictions were compared to experimental data both in the projection domain and in the reconstructed image. Noise prediction agreement between simulated and experimental data in terms of the root-mean-square (RMS) error was better than 7% for a homogeneous water phantom and a sensitometry phantom with tubular inserts. For an anthropomorphic head phantom, modeling the anatomy of a five-year-old child, the RMS error was better than 9% in three evaluated slices. We were able to reproduce subtle noise features near heterogeneities. To demonstrate the feasibility of Monte Carlo simulated noise maps for fluence modulation, we calculated a fluence profile that yields a homogeneous noise level in the image. Unlike for bow-tie filters in x-ray CT this does not require constant fluence at the detector and the shape of the fluence profile is fundamentally different. Using an improved Monte Carlo simulation, we demonstrated the feasibility of using simulated data for accurate image noise prediction for pCT. We believe that the agreement with experimental data is sufficient to enable the future optimization of FMpCT fluence plans to achieve prescribed noise targets in a fluence-modulated acquisition

Low-dose imaging for particle therapy with fluence-modulated proton computed tomography

Particle therapy for the curative treatment of tumors with energetic charged particles allows for the precise deposition of a therapeutic dose in the cancerous tissue while sparing surrounding healthy tissue. This exploits the increased dose deposition of charged particles, typically protons or carbon ions, at the end of their range. The treatment planning with highly conformal doses, however, requires a precise volumetric knowledge of the patients stopping power relative to water (RSP). In current clinical practice, such images are acquired using x-ray computed tomography, which measures the interaction of photons with matter and is subsequently converted to RSP. This conversion leads to errors, which need to be considered as additional margins around the tumor and necessarily lead to a higher dose to healthy tissue. An imaging modality suggested to reduce such errors is proton computed tomography (pCT), which directly determines the RSP through measurements of the energy loss of protons in the patient. Within this work, methods for dynamic modulation of the imaging fluence field have been established to reduce the imaging dose required for pCT acquisitions. With fluence-modulated pCT (FMpCT), the image is split into a region-of-interest (ROI), where good image quality is needed, and a non-ROI region, which is not used for treatment planning. In the context of particle therapy, the ROI covers the vicinity of the therapeutic beam. Outside of the ROI, imaging noise can be increased and imaging dose reduced. The calculation of modulated fluence patterns requires a forward model, that predicts the expected image noise for a given fluence setting. Such a forward model was realized using a Monte Carlo model of a specific pCT scanner and validated against experimental data. This allowed to carefully disentangle single contributions to pCT image noise, which was found to strongly depend on the heterogeneity of the object. Using the forward model, two FMpCT optimization algorithms were proposed: a simpler one, that only takes into account image variance, and a more sophisticated one, that considers both image noise and imaging dose objectives. The FMpCT scans were realized both in simulations and in experiments at the Chicago proton center using small fluence-modulated pencil beams, for which an interface to the control system needed to be established. Simulations were performed using anonymized x-ray CTs of patients undergoing photon therapy, and corresponding proton therapy treatment plans served for the definition of the imaging ROI. The imaging dose outside of the ROI could be reduced by 74% compared to scans at uniform imaging fluence and at the same peak noise level. The imaging dose to critical structures such as the eyes could further be pushed down using the optimization and dose savings up to 87% were achieved while maintaining the accuracy for treatment plan optimization on FMpCT images. In addition, two methods for artifact reduction with un-modulated pCT scans were developed, with one directly addressing the physical reason for artifacts by merging two datasets at different incident energies. The second artifact correction method was purely empirical and made no assumption on the origin of image artifacts. It used a scan of a custom-built phantom with known RSP and allowed to almost halve the mean absolute RSP error of a prototype pCT scanner by 46%. In this work, the development and experimental realization of optimized FMpCT scans together with the improved accuracy of pCT opened an interesting perspective: towards adaptive particle therapy with daily image guidance without accumulation of excessive patient doses in healthy tissue.Partikeltherapie zur kurativen Behandlung von Tumoren mit beschleunigten Ionen ermöglicht die präzise Verabreichung der therapeutischen Strahlendosis im Krebsgewebe während umliegendes, gesundes Gewebe geschont wird. Dabei nutzt man die erhöhte Dosisabgabe von geladenen Teilchen, typischerweise Protonen oder Kohlenstoffionen, am Ende ihrer Reichweite. Eine Bestrahlungsplanung mit hoch-konformen Dosisverteilungen erfordert jedoch eine präzise volumetrische Bildgebung des relativen Bremsvermögens (RSP) des Patienten. In der derzeitigen klinischen Praxis werden solche Schnittbilder mittels Röntgen-Computertomographie erstellt, und nachfolgend die dabei gemessene Interaktion von Photonen mit Materie in RSP umgerechnet. Diese Umrechnung führt zu Fehlern, welche bei der Bestrahlungsplanung als zusätzliches Toleranzvolumen berücksichtigt werden müssen und unumgänglich zu erhöhter Strahlendosis im gesunden Gewebe führen. Ein Bildgebungsverfahren, welches diese Fehler reduzieren kann, ist die Protonen-Computertomographie (pCT), bei der das RSP direkt durch Messung des Energieverlusts von Protonen im Patienten bestimmt wird. In dieser Arbeit wurden Methoden zur dynamischen Modulation der Bildgebungsfluenz etabliert, mit denen die Dosis von pCT-Aufnahmen reduziert werden kann. Für fluenz-modulierte pCT (FMpCT) wird das Bild eingeteilt in eine Zielregion (ROI), in der hohe Bildqualität benötigt wird, sowie das restliche Volumen, das zur weiteren Bestrahlungsplanung nicht benötigt wird. Im Kontext der Partikeltherapie entspricht die ROI einer Umgebung um den therapeutischen Strahl. Außerhalb der ROI kann das Bildrauschen erhöht und die Bildgebungsdosis reduziert werden. Die Berechnung von modulierten Fluenzverteilungen wird ermöglicht durch ein Modell des für eine gegebene Fluenzmodulation zu erwartenden Bildrauschens. Ein solches Modell wurde mit Hilfe einer Monte Carlo Simulation eines spezifischen pCT Scanners erstellt und mit experimentellen Daten validiert. Dadurch war es außerdem möglich, einzelne physikalische Beiträge zum pCT Bildrauschen zu isolieren. Für den Rauschwert spielte dabei die Heterogenität des Bildgebungsobjektes eine entscheidende Rolle. Basierend auf dem Rauschmodell wurden zwei FMpCT Optimierungsalgorithmen entwickelt: ein vereinfachter, bei dem lediglich das Bildrauschen berücksichtigt wird, und ein weiterentwickelter, mit dem sowohl gewünschte Bildrausch- als auch Bildgebungsdosis-Verteilungen erzielt werden können. FMpCT Aufnahmen wurden durch Modulation der Fluenz kleiner Strahlbündel sowohl in Simulationen als auch in Experimenten am Protonenzentrum in Chicago realisiert. Für die Experimente musste eine Schnittstelle zum Kontrollsystem des Beschleunigers etabliert werden. In Simulationen mit anonymisierten Röntgen-CTs von Photonentherapie-Patienten wurde die Bildgebungs-ROI basierend auf entsprechenden Protonen-Bestrahlungsplänen definiert. Die Bildgebungsdosis außerhalb der ROI wurde dabei um 74% reduziert im Vergleich zu Aufnahmen bei gleichmäßiger Fluenz und bei gleichem maximalen Rauschwert. Die Bildgebungsdosis in kritischen Strukturen wie den Augen konnte dabei im Rahmen der Optimierung weiter verringert werden und Reduktionen von bis zu 87% waren möglich. Dabei wurde die Genauigkeit der Bestrahlungsplanung nicht beeinträchtigt. Zusätzlich wurden zwei Methoden zur Artefaktkorrektur in nicht-modulierten pCT Aufnahmen entwickelt. Dabei berücksichtigte eine Methode direkt die physikalische Ursache von Bildgebungsartefakten und führte selektiv zwei Datensätze bei unterschiedlichen Protonenenergien zusammen. Die zweite Artefaktkorrektur war vollkommen empirisch und machte keine Annahmen über die Ursache der Artefakte. Dabei wurde eine Aufnahme eines eigens herstellten Phantoms mit bekanntem RSP genutzt. Mit der Methode wurde der mittlere absolute RSP-Fehler eines Prototypen-pCT-Scanners um 47% reduziert. Diese Arbeit hat mit der Entwicklung und experimentellen Realisierung von optimierten FMpCT Aufnahmen zusammen mit der verbesserten Genauigkeit von pCT eine interessante Perspektive eröffnet: hin zur adaptiven Partikeltherapie mit täglicher Bildgebung unter Vermeidung übermäßiger Dosisbelastung in gesundem Gewebe

Evaluation of the impact of a scanner prototype on proton CT and helium CT image quality and dose efficiency with Monte Carlo simulation

International audienceObjective. The use of ion computed tomography (CT) promises to yield improved relative stopping power (RSP) estimation as input to particle therapy treatment planning. Recently, proton CT (pCT) has been shown to yield RSP accuracy on par with state-of-the-art x-ray dual energy CT. There are however concerns that the lower spatial resolution of pCT compared to x-ray CT may limit its potential, which has spurred interest in the use of helium ion CT (HeCT). The goal of this study was to investigate image quality of pCT and HeCT in terms of noise, spatial resolution, RSP accuracy and imaging dose using a detailed Monte Carlo (MC) model of an existing ion CT prototype. Approach. Three phantoms were used in simulated pCT and HeCT scans allowing estimation of noise, spatial resolution and the scoring of dose. An additional phantom was used to evaluate RSP accuracy. The imaging dose required to achieve the same image noise in a water and a head phantom was estimated at both native spatial resolution, and in a scenario where the HeCT spatial resolution was reduced and matched to that of pCT using Hann windowing of the reconstruction filter. A variance reconstruction formalism was adapted to account for Hann windowing. Main results. We confirmed that the scanner prototype would produce higher spatial resolution for HeCT than pCT by a factor 1.8 (0.86 lp mm −1 versus 0.48 lp mm −1 at the center of a 20 cm water phantom). At native resolution, HeCT required a factor 2.9 more dose than pCT to achieve the same noise, while at matched resolution, HeCT required only 38% of the pCT dose. Finally, RSP mean absolute percent error (MAPE) was found to be 0.59% for pCT and 0.67% for HeCT. Significance. This work compared the imaging performance of pCT and HeCT when using an existing scanner prototype, with the spatial resolution advantage of HeCT coming at the cost of increased dose. When matching spatial resolution via Hann windowing, HeCT had a substantial dose advantage. Both modalities provided state-of-the-art RSP MAPE. HeCT might therefore help reduce the dose exposure of patients with comparable image noise to pCT, enhanced spatial resolution and acceptable RSP accuracy at the same time

Understanding image artifacts for a prototype proton computed tomography scanner via Monte Carlo simulations

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

International audienceProton 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 Monte Carlo simulations of an existing pCT scanner prototype, which we describe in detail

Dynamic Fluence Modulation using Proton CT for Low-dose Imaging in Particle Therapy

International audienceDynamic fluence modulation for computed tomography (CT), i.e. the acquisition of tomographic images with variable, patient-and task-specific fluence fields, offers the potential to substantially reduce local imaging dose. In particular, volume-of-interest (VOI) imaging allows to limit imaging dose to a clinically relevant volume and reduce it elsewhere. In the context of particle therapy, where tomographic data is required for treatment planning the VOI is the treatment beam path. VOI imaging is of particular interest for particle therapy given the very low integral out-of-VOI treatment dose. Proton CT imaging allows for a direct measurement of the proton stopping power with an increased accuracy and a decreased imaging dose compared to x-ray-based CT. In addition, frequent imaging is required to verify patient positioning and to monitor potential anatomical changes, which over the course of a treatment may compromise the planned dose. In this work, we evaluate the performance of a fluence-modulated proton CT algorithm for low-dose in-room imaging. This would allow for recalculation or replanning of the treatment dose according to the anatomy of the day with out-of-VOI dose below 1 mGy. We performed a simulation study and acquired experimental data using a prototype proton CT scanner. By employing a bow-tie-like fluence modulation aiming for constant noise, imaging dose was reduced by 9%. For a VOI imaging task, out-of-VOI dose was reduced by 41% and substantially below 1 mGy. This may pave the way for daily imaging prior to every treatment session aiming to eventually reduce safety margins in particle therapy, thus further reducing normal tissue exposure to therapeutic doses

Experimental realization of dynamic fluence field optimization for proton computed tomography

International audienceProton computed tomography (pCT) has high accuracy and dose efficiency in producing spatial maps of the relative stopping power (RSP) required for treatment planning in proton therapy. With fluence-modulated pCT (FMpCT), prescribed noise distributions can be achieved, which allows to decrease imaging dose by employing object-specific dynamically modulated fluence during the acquisition. For FMpCT acquisitions we divide the image into region-of-interest (ROI) and non-ROI volumes. In proton therapy, the ROI volume would encompass all treatment beams. An optimization algorithm then calculates dynamically modulated fluence that achieves low prescribed noise inside the ROI and high prescribed noise elsewhere. It also produces a planned noise distribution, which is the expected noise map for that fluence, as calculated with a Monte Carlo simulation. The optimized fluence can be achieved by acquiring pCT images with grids of intensity modulated pencil beams. In this work, we interfaced the control system of a clinical proton beam line to deliver the optimized fluence. Using three phantoms we acquired images with uniform fluence, with a constant noise prescription, and with an FMpCT task. Image noise distributions as well as fluence maps were compared to the corresponding planned distributions as well as to the prescription. Furthermore, we propose a correction method that removes image artifacts stemming from the acquisition with pencil beams having a spatially varying energy distribution that is not seen in clinical operation. RSP accuracy of FMpCT scans was compared to uniform scans and was found to be comparable to standard pCT scans. While we identified technical improvements for future experimental acquisitions, in particular related to an unexpected pencil beam size reduction and a misalignment of the fluence pattern, agreement with the planned noise was satisfactory and we conclude that FMpCT optimized for specific image noise prescriptions is experimentally feasible