Real-time dose reconstruction in proton therapy from in-beam PET measurements

Objective. Clinical implementation of in-beam positron emission tomography (PET) monitoring in proton therapy (PT) requires the integration of an online fast and reliable dose calculation engine. This manuscript reports on the achievement of real-time reconstruction of 3D dose and activity maps with proton range verification from experimental in-beam PET measurements.Approach. Several cylindrical homogeneous PMMA phantoms were irradiated with a monoenergetic 70 MeV proton beam in a clinical facility. Additionally, PMMA range-shifting foils of varying thicknesses were placed at the proximal surface of the phantom to investigate range shift prediction capabilities. PET activity was measured using a state-of-the-art in-house developed six-module PET scanner equipped with online PET reconstruction capabilities. For real-time dose estimation, we integrated this system with an in-beam dose estimation algorithm, which combines a graphical processing unit-based 3D reconstruction algorithm with a dictionary-based software, capable of estimating deposited doses from the 3D PET activity images. The range shift prediction performance has been quantitatively studied in terms of the minimum dose to be delivered and the maximum acquisition time.Main results. With this framework, 3D dose maps were accurately reconstructed and displayed with a delay as short as one second. For a dose fraction of 8.4 Gy at the Bragg peak maximum, range shifts as small as 1 mm could be detected. The quantitative analysis shows that accumulating 20 s of statistics from the start of the irradiation, doses down to 1 Gy could be estimated online with total uncertainties smaller than 2 mm.Significance. The hardware and software combination employed in this work can deliver dose maps and accurately predict range shifts after short acquisition times and small doses, suggesting that real-time monitoring and dose reconstruction during PT are within reach. Future work will focus on testing the methodology in more complex clinical scenarios and on upgrading the PET prototype for increased sensitivity.

Flexible and modular PET: Evaluating the potential of TOF-DOI panel detectors

BACKGROUND

Panel detectors have the potential to provide a flexible, modular approach to Positron Emission Tomography (PET), enabling customization to meet patient-specific needs and scan objectives. The panel design allows detectors to be positioned close to the patient, aiming to enhance sensitivity and spatial resolution through improved geometric coverage and reduced noncollinearity blurring. Parallax error can be mitigated using depth of interaction (DOI) information.

PURPOSE

One of the key questions the article addresses is: Do panel detectors offer viable clinical imaging capabilities, or does limited angular sampling restrict their utility by causing image distortions and artifacts? Additionally, this article explores the scalability of panel detectors for constructing scanners with a long axial field of view (LAFOV).

METHODS

Monte Carlo simulations using GATE software were used to assess the performance of panel detectors with various DOI resolutions and Time-of-Flight (TOF) resolutions as fine as 70 ps. The 30 × $\times$ 30 cm panels comprised pixelated 3 × $\times$ 3 × $\times$ 20 mm LSO crystals. Simulations were run on large high-performance computing clusters (122,000 CPU cores). Open-source CASToR software was used for (TOF MLEM) image reconstruction. The image quality of the scanners was assessed using a range of phantoms (NEMA, Derenzo, XCAT, and a high-resolution brain phantom). The Siemens Biograph Vision PET/CT scanner served as the reference model. The performance of larger 120 × $\times$ 60 cm panels was also evaluated.

RESULTS

Sensitivity increases over threefold when panel-panel distance is reduced from 80 to 40 cm. The noise equivalent count rate, unmodified by TOF gain, of the panel detectors matches that of the reference clinical scanner at a distance of approximately 50 cm between the panels. Spatial resolution perpendicular to the panels improves from 8.7 to 1.6 mm when the panel-panel distance is reduced, and 70 ps + DOI detectors are used instead of 200 ps, no-DOI detectors. With enhanced TOF and DOI capabilities, panel detectors achieve image quality that matches or surpasses the reference scanner while using about four times less detector material. These detectors can be extended for LAFOV imaging without distortions or artifacts. Additionally, improving TOF and DOI performance enhances contrast-to-noise ratios, thereby improving lesion detection.

CONCLUSIONS

A compact 2-panel PET scanner can match the performance of conventional scanners, producing high-quality, distortion-free images. Its mobility and flexibility enable novel applications, including bedside imaging and intensive care unitdiagnostics, as well as imaging in positions such as sitting or standing. Furthermore, the modularity of panel detectors offers the potential to construct cost-effective, high-performance total-body imaging systems.

Development and evaluation of an in-beam PET system for proton therapy monitoring

Objective. In-beam positron emission tomography (PET) has important development prospects in real-time monitoring of proton therapy. However, in the beam-on operation, the high bursts of radiation events pose challenges to the performance of the PET system.Approach. In this study, we developed a dual-head in-beam PET system for proton therapy monitoring and evaluated its performance. The system has two PET detection heads, each with6×3Plug&Imaging (PnI) detection units. Each PnI unit consists of6×6lutetium-yttrium oxyorthosilicate crystal arrays. The size of each crystal strip is3.95×3.95×20 mm3, which is one-to-one coupled with a silicon photomultiplier. The overall size of the head is15.3×7.65 cm2.Main results. The in-beam PET system achieved a single count rate of 48 Mcps at the activity of 144.9 MBq, an absolute sensitivity of 2.717%, and a spatial resolution of approximately 2.6 mm (full width at half maximum) at the center of the field-of-view. When imaging a Derenzo phantom, the system could resolve rods with a diameter of 2.0 mm. Time-dynamic [18F]-Fluorodeoxyglucose mouse imaging was performed, demonstrating the metabolic processes in the mouse. This shows that the in-beam PET system has the potential for biology-guided proton therapy. The in-beam PET system was used to monitor the range of a 130 MeV proton beam irradiating a polymethyl methacrylate (PMMA) phantom, with a beam intensity of6.0×109p s-1and an irradiation duration of one minute. PET data were acquired only during the one-minute irradiation. We simulated the range shift by moving the PMMA and adding an air gap, showing that the error between the actual and the measured range is less than 1 mm.Significance. The results demonstrate that the system has a high count rate and the capability of range monitoring in beam-on operation, which is beneficial for achieving real-time range verification of proton beams in the future.

Proton spot dose estimation based on positron activity distributions with neural network

BACKGROUND

Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy.

PURPOSE

This study evaluates the effectiveness of three classical neural network models, recurrent neural network (RNN), U-Net, and Transformer, for proton dose estimating. It also investigates the characteristics of these models, providing valuable insights for selecting the appropriate model in clinical practice.

METHODS

Proton dose calculations for spot beams were simulated using Geant4. Computed tomography (CT) images from four head cases were utilized, with three for training neural networks and the remaining one for testing. The neural networks were trained with one-dimensional (1D) positron activity distributions as inputs and generated 1D dose distributions as outputs. The impact of the number of training samples on the networks was examined, and their dose prediction performance in both homogeneous brain and heterogeneous nasopharynx sites was evaluated. Additionally, the effect of positron activity distribution uncertainty on dose prediction performance was investigated. To quantitatively evaluate the models, mean relative error (MRE) and absolute range error (ARE) were used as evaluation metrics.

RESULTS

The U-Net exhibited a notable advantage in range verification with a smaller number of training samples, achieving approximately 75% of AREs below 0.5 mm using only 500 training samples. The networks performed better in the homogeneous brain site compared to the heterogeneous nasopharyngeal site. In the homogeneous brain site, all networks exhibited small AREs, with approximately 90% of the AREs below 0.5 mm. The Transformer exhibited the best overall dose distribution prediction, with approximately 92% of MREs below 3%. In the heterogeneous nasopharyngeal site, all networks demonstrated acceptable AREs, with approximately 88% of AREs below 3 mm. The Transformer maintained the best overall dose distribution prediction, with approximately 85% of MREs below 5%. The performance of all three networks in dose prediction declined as the uncertainty of positron activity distribution increased, and the Transformer consistently outperformed the other networks in all cases.

CONCLUSIONS

Both the U-Net and the Transformer have certain advantages in the proton dose estimation task. The U-Net proves well suited for range verification with a small training sample size, while the Transformer outperforms others at dose-guided proton therapy.

Measurement of the12C(p,n)12N reaction cross section below 150 MeV

Objective. Proton therapy currently faces challenges from clinical complications on organs-at-risk due to range uncertainties. To address this issue, positron emission tomography (PET) of the proton-induced11C and15O activity has been used to provide feedback on the proton range. However, this approach is not instantaneous due to the relatively long half-lives of these nuclides. An alternative nuclide,12N (half-life 11 ms), shows promise for real-timein vivoproton range verification. Development of12N imaging requires better knowledge of its production reaction cross section.Approach. The12C(p,n)12N reaction cross section was measured by detecting positron activity of graphite targets irradiated with 66.5, 120, and 150 MeV protons. A pulsed beam delivery with 0.7-2 × 108protons per pulse was used. The positron activity was measured during the beam-off periods using a dual-head Siemens Biograph mCT PET scanner. The12N production was determined from activity time histograms.Main results. The cross section was calculated for 11 energies, ranging from 23.5 to 147 MeV, using information on the experimental setup and beam delivery. Through a comprehensive uncertainty propagation analysis, a statistical uncertainty of 2.6%-5.8% and a systematic uncertainty of 3.3%-4.6% were achieved. Additionally, a comparison between measured and simulated scanner sensitivity showed a scaling factor of 1.25 (±3%). Despite this, there was an improvement in the precision of the cross section measurement compared to values reported by the only previous study.Significance. Short-lived12N imaging is promising for real-timein vivoverification of the proton range to reduce clinical complications in proton therapy. The verification procedure requires experimental knowledge of the12N production cross section for proton energies of clinical importance, to be incorporated in a Monte Carlo framework for12N imaging prediction. This study is the first to achieve a precise measurement of the12C(p,n)12N nuclear cross section for such proton energies.