Resolution enhancement, noise suppression, and joint T2* decay estimation in dual-echo sodium-23 MR imaging using anatomically guided reconstruction.

PURPOSE: Sodium MRI is challenging because of the low tissue concentration of the 23 Na nucleus and its extremely fast biexponential transverse relaxation rate. In this article, we present an iterative reconstruction framework using dual-echo 23 Na data and exploiting anatomical prior information (AGR) from high-resolution, low-noise, 1 H MR images. This framework enables the estimation and modeling of the spatially varying signal decay due to transverse relaxation during readout (AGRdm), which leads to images of better resolution and reduced noise resulting in improved quantification of the reconstructed 23 Na images. METHODS: The proposed framework was evaluated using reconstructions of 30 noise realizations of realistic simulations of dual echo twisted projection imaging (TPI) 23 Na data. Moreover, three dual echo 23 Na TPI brain datasets of healthy controls acquired on a 3T Siemens Prisma system were reconstructed using conventional reconstruction, AGR and AGRdm. RESULTS: Our simulations show that compared to conventional reconstructions, AGR and AGRdm show improved bias-noise characteristics in several regions of the brain. Moreover, AGR and AGRdm images show more anatomical detail and less noise in the reconstructions of the experimental data sets. Compared to AGR and the conventional reconstruction, AGRdm shows higher contrast in the sodium concentration ratio between gray and white matter and between gray matter and the brain stem. CONCLUSION: AGR and AGRdm generate 23 Na images with high resolution, high levels of anatomical detail, and low levels of noise, potentially enabling high-quality 23 Na MR imaging at 3T.

The SNR of time-of-flight positron emission tomography data for joint reconstruction of the activity and attenuation images.

Objective.Measurement of the time-of-flight (TOF) difference of each coincident pair of photons increases the effective sensitivity of positron emission tomography (PET). Many authors have analyzed the benefit of TOF for quantification and hot spot detection in the reconstructed activity images. However, TOF not only improves the effective sensitivity, it also enables the joint reconstruction of the tracer concentration and attenuation images. This can be used to correct for errors in CT- or MR-derived attenuation maps, or to apply attenuation correction without the help of a second modality. This paper presents an analysis of the effect of TOF on the variance of the jointly reconstructed attenuation and (attenuation corrected) tracer concentration images.Approach.The analysis is performed for PET systems that have a distribution of possibly non-Gaussian TOF-kernels, and includes the conventional Gaussian TOF-kernel as a special case. Non-Gaussian TOF-kernels are often observed in novel detector designs, which make use of two (or more) different mechanisms to convert the incoming 511 keV photon to optical photons. The analytical result is validated with a simple 2D simulation.Main results.We show that if two different TOF-kernels are equivalent for image reconstruction with known attenuation, then they are also equivalent for joint reconstruction of the activity and the attenuation images. The variance increase in the activity, caused by also jointly reconstructing the attenuation image, vanishes when the TOF-resolution approaches perfection.Significance.These results are of interest for PET detector development and for the development of stand-alone PET systems.

The SNR of Positron Emission Data With Gaussian and Non-Gaussian Time-of-Flight Kernels, With Application to Prompt Photon Coincidence.

It is well known that measurement of the time-of-flight (TOF) increases the information provided by coincident events in positron emission tomography (PET). This information increase propagates through the reconstruction and improves the signal-to-noise ratio in the reconstructed images. Takehiro Tomitani has analytically computed the gain in variance in the reconstructed image, provided by a particular TOF resolution, for the center of a uniform disk and for a Gaussian TOF kernel. In this paper we extend this result, by computing the signal-to-noise ratio (SNR) contributed by individual coincidence events for two different tasks. One task is the detection of a hot spot in the center of a uniform cylinder. The second one is the same as that considered by Tomitani, i.e. the reconstruction of the central voxel in the image of a uniform cylinder. In addition, we extend the computation to non-Gaussian TOF kernels. It is found that a modification of the TOF-kernel changes the SNR for both tasks in almost exactly the same way. The proposed method can be used to compare TOF-systems with different and possibly event-dependent TOF-kernels, as encountered when prompt photons, such as Cherenkov photons are present, or when the detector is composed of different scintillators. The method is validated with simple 2D simulations and illustrated by applying it to PET detectors producing optical photons with event-dependent timing characteristics.

An optically-guided cochlear implant sheath for real-time monitoring of electrode insertion into the human cochlea.

In cochlear implant surgery, insertion of perimodiolar electrode arrays into the scala tympani can be complicated by trauma or even accidental translocation of the electrode array within the cochlea. In patients with partial hearing loss, cochlear trauma can not only negatively affect implant performance, but also reduce residual hearing function. These events have been related to suboptimal positioning of the cochlear implant electrode array with respect to critical cochlear walls of the scala tympani (modiolar wall, osseous spiral lamina and basilar membrane). Currently, the position of the electrode array in relation to these walls cannot be assessed during the insertion and the surgeon depends on tactile feedback, which is unreliable and often comes too late. This study presents an image-guided cochlear implant device with an integrated, fiber-optic imaging probe that provides real-time feedback using optical coherence tomography during insertion into the human cochlea. This novel device enables the surgeon to accurately detect and identify the cochlear walls ahead and to adjust the insertion trajectory, avoiding collision and trauma. The functionality of this prototype has been demonstrated in a series of insertion experiments, conducted by experienced cochlear implant surgeons on fresh-frozen human cadaveric cochleae.

Experimental validation of a rodent PET scanner prototype based on a single LYSO crystal tube.

Improving sensitivity and spatial resolution in small animal Positron Emission Tomography imaging instrumentation constitutes one of the main goals of nuclear imaging research. These parameters are degraded by the presence of gaps between the detectors. The present manuscript experimentally validates our prototype of an edge-less pre-clinical PET system based on a single LYSO:Ce annulus with an inner diameter of 62 mm and 10 outer facets of 26 × 52 mm2. Scintillation light is read out by arrays of 8 × 8 SiPMs coupled to the facets, using a projection readout of the rows and columns signals. The readout provides accurate Depth of Interaction (DOI). We have implemented a calibration that mitigates the DOI-dependency of the transaxial and axial impact coordinates, and the energy photopeak gain. An energy resolution of 23.4 ± 1.8% was determined. Average spatial resolution of 1.4 ± 0.2 and 1.3 ± 0.4 mm FWHM were achieved for the radial and axial directions, respectively. We found a peak sensitivity of 3.8% at the system center, and a maximum NECR at 40.6 kcps for 0.27 mCi. The image quality was evaluated using reconstructed images of an array of sources and the NEMA image quality phantom was also studied.

Low-dose CT allows for accurate proton therapy dose calculation and plan optimization.

Objective.Protons offer a more conformal dose delivery compared to photons, yet they are sensitive to anatomical changes over the course of treatment. To minimize range uncertainties due to anatomical variations, a new CT acquisition at every treatment session would be paramount to enable daily dose calculation and subsequent plan adaptation. However, the series of CT scans results in an additional accumulated patient dose. Reducing CT radiation dose and thereby decreasing the potential risk of radiation exposure to patients is desirable, however, lowering the CT dose results in a lower signal-to-noise ratio and therefore in a reduced quality image. We hypothesized that the signal-to-noise ratio provided by conventional CT protocols is higher than needed for proton dose distribution estimation. In this study, we aim to investigate the effect of CT imaging dose reduction on proton therapy dose calculations and plan optimization.Approach.To verify our hypothesis, a CT dose reduction simulation tool has been developed and validated to simulate lower-dose CT scans from an existing standard-dose scan. The simulated lower-dose CTs were then used for proton dose calculation and plan optimization and the results were compared with those of the standard-dose scan. The same strategy was adopted to investigate the effect of CT dose reduction on water equivalent thickness (WET) calculation to quantify CT noise accumulation during integration along the beam.Main results.The similarity between the dose distributions acquired from the low-dose and standard-dose CTs was evaluated by the dose-volume histogram and the 3D Gamma analysis. The results on an anthropomorphic head phantom and three patient cases indicate that CT imaging dose reduction up to 90% does not have a significant effect on proton dose calculation and plan optimization. The relative error was employed to evaluate the similarity between WET maps and was found to be less than 1% after reducing the CT imaging dose by 90%.Significance.The results suggest the possibility of using low-dose CT for proton therapy dose estimation, since the dose distributions acquired from the standard-dose and low-dose CTs are clinically equivalent.

Can nuclear imaging accurately detect scar in ischemic cardiac resynchronization therapy candidates?

BACKGROUND: Accurate scar assessment is crucial in cardiac resynchronization therapy (CRT) candidates, since its presence is a negative predictor for CRT response. Therefore, we assessed the performance of different PET parameters to detect scar in CRT candidates. METHODS: Twenty-nine CRT candidates underwent 18F-fluorodeoxyglucose (18F-FDG)-PET/computed tomography (CT), resting 13N-NH3-PET/CT and cardiac magnetic resonance (CMR) prior to CRT implantation. Segmental 18F-FDG uptake, late 13N-NH3 uptake and absolute myocardial blood flow (MBF) were evaluated for scar detection using late gadolinium enhancement (LGE) CMR as reference. A receiver operator characteristic (ROC) area under the curve (AUC) ≥0.8 indicated a good accuracy of the methods evaluated. RESULTS: Scar was present in 111 of 464 segments. None of the approaches could reliably identify segments with nontransmural scar, except for 18F-FDG uptake in the lateral wall (AUC 0.83). Segmental transmural scars could be detected with all methods (AUC ≥ 0.8), except for septal 18F-FDG uptake and MBF in the inferior wall (AUC < 0.8). Late 13N-NH3 uptake was the best parameter for transmural scar detection, independent of its location, with a sensitivity of 80% and specificity of 92% using a cutoff of 66% of the maximum tracer activity. CONCLUSIONS: Late 13N-NH3 uptake is superior to 13N-NH3 MBF and 18F-FDG in detecting transmural scar, independently of its location. However, none of the tested PET parameters was able to accurately detect nontransmural scar.

Segmentation-guided multi-modal registration of liver images for dose estimation in SIRT.

PURPOSE: Selective internal radiation therapy (SIRT) requires a good liver registration of multi-modality images to obtain precise dose prediction and measurement. This study investigated the feasibility of liver registration of CT and MR images, guided by segmentation of the liver and its landmarks. The influence of the resulting lesion registration on dose estimation was evaluated. METHODS: The liver segmentation was done with a convolutional neural network (CNN), and the landmarks were segmented manually. Our image-based registration software and its liver-segmentation-guided extension (CNN-guided) were tuned and evaluated with 49 CT and 26 MR images from 20 SIRT patients. Each liver registration was evaluated by the root mean square distance (RMSD) of mean surface distance between manually delineated liver contours and mass center distance between manually delineated landmarks (lesions, clips, etc.). The root mean square of RMSDs (RRMSD) was used to evaluate all liver registrations. The CNN-guided registration was further extended by incorporating landmark segmentations (CNN&LM-guided) to assess the value of additional landmark guidance. To evaluate the influence of segmentation-guided registration on dose estimation, mean dose and volume percentages receiving at least 70 Gy (V70) estimated on the 99mTc-labeled macro-aggregated albumin (99mTc-MAA) SPECT were computed, either based on lesions from the reference 99mTc-MAA CT (reference lesions) or from the registered floating CT or MR images (registered lesions) using the CNN- or CNN&LM-guided algorithms. RESULTS: The RRMSD decreased for the floating CTs and MRs by 1.0 mm (11%) and 3.4 mm (34%) using CNN guidance for the image-based registration and by 2.1 mm (26%) and 1.4 mm (21%) using landmark guidance for the CNN-guided registration. The quartiles for the relative mean dose difference (the V70 difference) between the reference and registered lesions and their correlations [25th, 75th; r] are as follows: [- 5.5% (- 1.3%), 5.6% (3.4%); 0.97 (0.95)] and [- 12.3% (- 2.1%), 14.8% (2.9%); 0.96 (0.97)] for the CNN&LM- and CNN-guided CT to CT registrations, [- 7.7% (- 6.6%), 7.0% (3.1%); 0.97 (0.90)] and [- 15.1% (- 11.3%), 2.4% (2.5%); 0.91 (0.78)] for the CNN&LM- and CNN-guided MR to CT registrations. CONCLUSION: Guidance by CNN liver segmentations and landmarks markedly improves the performance of the image-based registration. The small mean dose change between the reference and registered lesions demonstrates the feasibility of applying the CNN&LM- or CNN-guided registration to volume-level dose prediction. The CNN&LM- and CNN-guided registrations for CTs can be applied to voxel-level dose prediction according to their small V70 change for most lesions. The CNN-guided MR to CT registration still needs to incorporate landmark guidance for smaller change of voxel-level dose estimation.

Design and modeling of a high resolution and high sensitivity PET brain scanner with double-ended readout.

In the wake of recent advancements in scintillator, photodetector, and low-noise fast electronics technologies, as well as in fast reconstruction software, positron emission tomography (PET) scanners have seen considerable improvements in spatial resolution, time resolution, and absolute sensitivity. To continue this trend, we present a helmet type PET brain scanner design that combines high solid angle coverage and double-ended readout of 30 mm-thick scintillator crystals to achieve excellent absolute sensitivity, depth of interaction resolution, and time resolution. This scanner comprises 598 detector arrays, each with 8 × 8 Lu1.8Y0.2SiO5:Ce (LYSO:Ce) crystals with dimensions 3.005 × 3.005 × 30 mm3one-to-one coupled on either end to silicon photomultipliers (SiPMs). Our Monte Carlo simulations based in the platform Geant4 predict that this scanner would attain an absolute sensitivity to a 35 cm line source placed at the center of the radial field of view of (17.1 ± 0.1)%, a depth of interaction resolution of (3.99 ± 0.05) mm, and a coincidence time resolution of (198 ± 5) ps. Our simulations also predict radial, tangential, and axial spatial resolutions at the center of the field of view of 3.3 mm, 3.1 mm, and 3.3 mm, respectively. As this set of simultaneous parameters compares favorably to today's most advanced clinical PET scanners and other proposed designs, this scanner has a good chance of becoming a preferred tool for high quality brain imaging.

2D feasibility study of joint reconstruction of attenuation and activity in limited angle TOF-PET.

Several research groups are studying organ-dedicated limited angle positron emission tomography (PET) systems to optimize performance-cost ratio, sensitivity, access to the patient and/or flexibility. Often open systems are considered, typically consisting of two detector panels of various sizes. Such systems provide incomplete sampling due to limited angular coverage and/or truncation, which leads to artefacts in the reconstructed activity images. In addition, these organ-dedicated PET systems are usually stand-alone systems, and as a result, no attenuation information can be obtained from anatomical images acquired in the same imaging session. It has been shown that the use of time-of-flight information reduces incomplete data artefacts and enables the joint estimation of the activity and the attenuation factors. In this work, we explore with simple 2D simulations the performance and stability of a joint reconstruction algorithm, for imaging with a limited angle PET system. The reconstruction is based on the so-called MLACF (Maximum Likelihood Attenuation Correction Factors) algorithm and uses linear attenuation coefficients in a known-tissue-class region to obtain absolute quantification. Different panel sizes and different time-of-flight (TOF) resolutions are considered. The noise propagation is compared to that of MLEM reconstruction with exact attenuation correction (AC) for the same PET system. The results show that with good TOF resolution, images of good visual quality can be obtained. If also a good scatter correction can be implemented, quantitative PET imaging will be possible. Further research, in particular on scatter correction, is required.

Time of Flight in Perspective: Instrumental and Computational Aspects of Time Resolution in Positron Emission Tomography.

The first time-of-flight positron emission tomography (TOF-PET) scanners were developed as early as in the 1980s. However, the poor light output and low detection efficiency of TOF-capable detectors available at the time limited any gain in image quality achieved with these TOF-PET scanners over the traditional non-TOF PET scanners. The discovery of LSO and other Lu-based scintillators revived interest in TOF-PET and led to the development of a second generation of scanners with high sensitivity and spatial resolution in the mid-2000s. The introduction of the silicon photomultiplier (SiPM) has recently yielded a third generation of TOF-PET systems with unprecedented imaging performance. Parallel to these instrumentation developments, much progress has been made in the development of image reconstruction algorithms that better utilize the additional information provided by TOF. Overall, the benefits range from a reduction in image variance (SNR increase), through allowing joint estimation of activity and attenuation, to better reconstructing data from limited angle systems. In this work, we review these developments, focusing on three broad areas: 1) timing theory and factors affecting the time resolution of a TOF-PET system; 2) utilization of TOF information for improved image reconstruction; and 3) quantification of the benefits of TOF compared to non-TOF PET. Finally, we offer a brief outlook on the TOF-PET developments anticipated in the short and longer term. Throughout this work, we aim to maintain a clinically driven perspective, treating TOF as one of multiple (and sometimes competitive) factors that can aid in the optimization of PET imaging performance.

Rigid motion tracking using moments of inertia in TOF-PET brain studies.

A data-driven method is proposed for rigid motion estimation directly from time-of-flight (TOF)-positron emission tomography (PET) emission data. Rigid motion parameters (translations and rotations) are estimated from the first and second moments of the emission data masked in a spherical volume. The accuracy of the method is analyzed on 3D analytical simulations of the PET-SORTEO brain phantom, and subsequently tested on18F-FDG as well as11C-PIB brain datasets acquired on a TOF-PET/CT scanner. The estimated inertia-based motion is later compared to rigid motion parameters obtained by directly registering the short frame backprojections. We find that the method provides sub mm/degree accuracies for the estimated rigid motion parameters for counts corresponding to typical 0.5 s, 1 s, and 2 s18F-FDG brain scans, with the current TOF resolutions clinically available. The method provides robust motion estimation for different types of patient motion, most notably for a continuous patient motion case where conventional frame-based approaches which rely on little to no intra-frame motion of short time intervals could fail. The method relies on the detection of stable eigenvectors for accurate motion estimation, and a monitoring of this condition can reveal time-frames where the motion estimation is less accurate, such as in dynamic PET studies.

Gamma Camera Imaging with Rotating Multi-Pinhole Collimator. A Monte Carlo Feasibility Study.

In this work, we propose and analyze a new concept of gamma ray imaging that corresponds to a gamma camera with a mobile collimator, which can be used in vivo, during surgical interventions for oncological patients for localizing regions of interest such as tumors or ganglia. The benefits are a much higher sensitivity, better image quality and, consequently, a dose reduction for the patient and medical staff. This novel approach is a practical solution to the overlapping problem which is inherent to multi-pinhole gamma camera imaging and single photon emission computed tomography and which translates into artifacts and/or image truncation in the final reconstructed image. The key concept consists in introducing a relative motion between the collimator and the detector. Moreover, this design could also be incorporated into most commercially available gamma camera devices, without any excessive additional requirements. We use Monte Carlo simulations to assess the feasibility of such a device, analyze three possible designs and compare their sensitivity, resolution and uniformity. We propose a final design of a gamma camera with a high sensitivity ranging from 0.001 to 0.006 cps/Bq, and a high resolution of 0.5-1.0 cm (FWHM), for source-to-detector distances of 4-10 cm. Additionally, this planar gamma camera provides information about the depth of source (with approximate resolution of 1.5 cm) and excellent image uniformity.

A motion correction approach for oral and maxillofacial cone-beam CT imaging.

Patient movement affects image quality in oral and maxillofacial cone-beam computed tomography imaging. While many efforts are made to minimize the possibility of motion during a scan, relatively little attention has been given to motion correction after acquisition. We propose a novel method which can improve the image quality after an oral and maxillofacial scan. The proposed method is based on our previous work and is a retrospective motion estimation and motion compensation (ME/MC) approach that iteratively estimates and compensates for rigid pose change over time. During motion estimation, image update and motion update are performed alternately in a multi-resolution scheme to obtain the motion. We propose use of a feature-based motion update and patch-based image update in the iterative estimation process, to alleviate the effect of limited scan field of view on estimation. During motion compensation, a fine-resolution image reconstruction was performed with compensation for the estimated motion. The proposed ME/MC method was evaluated with simulations, phantom and patient studies. Two experts in dentomaxillofacial radiology assessed the diagnostic importance of the resulting motion artifact suppression. The quality of the reconstructed images was improved after motion compensation, and most of the image artifacts were eliminated. Quantitative analysis by comparison to a reference image and by calculation of a sharpness metric agreed with the qualitative observation. The results are promising, and further evaluation is required to assess the clinical value of the proposed method.

Left ventricular regional glucose metabolism in combination with septal scar extent identifies CRT responders.

BACKGROUND: Cardiac resynchronization therapy (CRT) is effective in selective heart failure (HF) patients, but non-response rate remains high. Positron emission tomography (PET) may provide a better insight into the pathophysiology of left ventricular (LV) remodeling; however, its role for evaluating and selecting patients for CRT remains uncertain. PURPOSE: We investigated if regional LV glucose metabolism in combination with myocardial scar could predict response to CRT. METHODS: Consecutive CRT-eligible HF patients underwent echocardiography, cardiac magnetic resonance (CMR), and 18F-fluorodeoxyglucose (FDG) PET within 1 week before CRT implantation. Echocardiography was additionally performed 12 months after CRT and end-systolic volume reduction ≥ 15% was defined as CRT response. Septal-to-lateral wall (SLR) FDG uptake ratio was calculated from static FDG images. Late gadolinium enhancement (LGE) CMR was analyzed semi-quantitatively to define scar extent. RESULTS: We evaluated 88 patients (67 ± 10 years, 72% males). 18F-FDG SLR showed a linear correlation with volumetric reverse remodeling 12 months after CRT (r = 0.41, p = 0.0001). In non-ischemic HF patients, low FDG SLR alone predicted CRT response with sensitivity and specificity of more than 80%; however, in ischemic HF patients, specificity decreased to 46%, suggesting that in this cohort low SLR can also be caused by the presence of a septal scar. In the multivariate logistic regression model, including low FDG SLR, presence and extent of the scar in each myocardial wall, and current CRT guideline parameters, only low FDG SLR and septal scar remained associated with CRT response. Their combination could predict CRT response with sensitivity, specificity, negative, and positive predictive value of 80%, 83%, 70%, and 90%, respectively. CONCLUSIONS: FDG SLR can be used as a predictor of CRT response and combined with septal scar extent, CRT responders can be distinguished from non-responders with high diagnostic accuracy. Further studies are needed to verify whether this imaging approach can prospectively be used to optimize patient selection.

Impact of left bundle branch block on myocardial perfusion and metabolism: A positron emission tomography study.

BACKGROUND: Better understanding of pathophysiological changes, induced by left bundle branch block (LBBB), may improve patient selection for cardiac resynchronization therapy (CRT). Therefore, we assessed the effect of LBBB on regional glucose metabolism, 13N-NH3-derived absolute and semiquantitative myocardial blood flow (MBF), and their relation in non-ischemic CRT candidates. METHODS: Twenty-five consecutive non-ischemic patients with LBBB underwent 18F-FDG and resting dynamic 13N-NH3 PET/CT prior to CRT implantation. Regional 18F-FDG uptake, absolute MBF, and late 13N-NH3 uptake were analyzed and corresponding septal-to-lateral wall ratios (SLR) were calculated. Segmental analysis was performed to evaluate "reverse mismatch," "mismatch," and "match" patterns, based on late 13N-NH3/18F-FDG uptake ratios. RESULTS: A significantly lower 18F-FDG uptake was observed in the septum compared to the lateral wall (SLR 0.53 ± 0.17). A similar pattern was observed for MBF (SLR 0.68 ± 0.18), whereas late 13N-NH3 uptake showed a homogeneous distribution (SLR 0.96 ± 0.13). 13N-NH3/18F-FDG "mismatch" and "reverse mismatch" segments were predominantly present in the lateral (52%) and septal wall (61%), respectively. CONCLUSIONS: Non-ischemic CRT candidates with LBBB demonstrate lower glucose uptake and absolute MBF in the septum compared to the lateral wall. However, late static 13N-NH3 uptake showed a homogenous distribution, reflecting a composite measure of altered regional MBF and metabolism, induced by LBBB.

Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network.

In the last two decades, it has been shown that anatomically-guided PET reconstruction can lead to improved bias-noise characteristics in brain PET imaging. However, despite promising results in simulations and first studies, anatomically-guided PET reconstructions are not yet available for use in routine clinical because of several reasons. In light of this, we investigate whether the improvements of anatomically-guided PET reconstruction methods can be achieved entirely in the image domain with a convolutional neural network (CNN). An entirely image-based CNN post-reconstruction approach has the advantage that no access to PET raw data is needed and, moreover, that the prediction times of trained CNNs are extremely fast on state of the art GPUs which will substantially facilitate the evaluation, fine-tuning and application of anatomically-guided PET reconstruction in real-world clinical settings. In this work, we demonstrate that anatomically-guided PET reconstruction using the asymmetric Bowsher prior can be well-approximated by a purely shift-invariant convolutional neural network in image space allowing the generation of anatomically-guided PET images in almost real-time. We show that by applying dedicated data augmentation techniques in the training phase, in which 16 [18F]FDG and 10 [18F]PE2I data sets were used, lead to a CNN that is robust against the used PET tracer, the noise level of the input PET images and the input MRI contrast. A detailed analysis of our CNN in 36 [18F]FDG, 18 [18F]PE2I, and 7 [18F]FET test data sets demonstrates that the image quality of our trained CNN is very close to the one of the target reconstructions in terms of regional mean recovery and regional structural similarity.

Quantitative PET in the 2020s: a roadmap.

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

Quantitative comparison of pre-treatment predictive and post-treatment measured dosimetry for selective internal radiation therapy using cone-beam CT for tumor and liver perfusion territory definition.

BACKGROUND: Selective internal radiation therapy (SIRT) is a promising treatment for unresectable hepatic malignancies. Predictive dose calculation based on a simulation using 99mTc-labeled macro-aggregated albumin (99mTc-MAA) before the treatment is considered as a potential tool for patient-specific treatment planning. Post-treatment dose measurement is mainly performed to confirm the planned absorbed dose to the tumor and non-tumor liver volumes. This study compared the predicted and measured absorbed dose distributions. METHODS: Thirty-one patients (67 tumors) treated by SIRT with resin microspheres were analyzed. Predicted and delivered absorbed dose was calculated using 99mTc-MAA-SPECT and 90Y-TOF-PET imaging. The voxel-level dose distribution was derived using the local deposition model. Liver perfusion territories and tumors have been delineated on contrast-enhanced CBCT images, which have been acquired during the 99mTc-MAA work-up. Several dose-volume histogram (DVH) parameters together with the mean dose for liver perfusion territories and non-tumoral and tumoral compartments were evaluated. RESULTS: A strong correlation between the predicted and measured mean dose for non-tumoral volume was observed (r = 0.937). The ratio of measured and predicted mean dose to this volume has a first, second, and third interquartile range of 0.83, 1.05, and 1.25. The difference between the measured and predicted mean dose did not exceed 11 Gy. The correlation between predicted and measured mean dose to the tumor was moderate (r = 0.623) with a mean difference of - 9.3 Gy. The ratio of measured and predicted tumor mean dose had a median of 1.01 with the first and third interquartile ranges of 0.58 and 1.59, respectively. Our results suggest that 99mTc-MAA-based dosimetry could predict under or over dosing of the non-tumoral liver parenchyma for almost all cases. For more than two thirds of the tumors, a predictive absorbed dose correctly indicated either good tumor dose coverage or under-dosing of the tumor. CONCLUSION: Our results highlight the predictive value of 99mTc-MAA-based dose estimation to predict non-tumor liver irradiation, which can be applied to prescribe an optimized activity aiming at avoiding liver toxicity. Compared to non-tumoral tissue, a poorer agreement between predicted and measured absorbed dose is observed for tumors.

Characterization of a preclinical PET insert in a 7 tesla MRI scanner: beyond NEMA testing.

This study evaluates the performance of the Bruker positron emission tomograph (PET) insert combined with a BioSpec 70/30 USR magnetic resonance imaging (MRI) scanner using the manufacturer acceptance protocol and the NEMA NU 4-2008 for small animal PET. The PET insert is made of 3 rings of 8 monolithic LYSO crystals (50 × 50 × 10 mm3) coupled to silicon photomultipliers (SiPM) arrays, conferring an axial and transaxial FOV of 15 cm and 8 cm. The MRI performance was evaluated with and without the insert for the following radiofrequency noise, magnetic field homogeneity and image quality. For the PET performance, we extended the NEMA protocol featuring system sensitivity, count rates, spatial resolution and image quality to homogeneity and accuracy for quantification using several MRI sequences (RARE, FLASH, EPI and UTE). The PET insert does not show any adverse effect on the MRI performances. The MR field homogeneity is well preserved (Diameter Spherical Volume, for 20 mm of 1.98 ± 4.78 without and -0.96 ± 5.16 Hz with the PET insert). The PET insert has no major effect on the radiofrequency field. The signal-to-noise ratio measurements also do not show major differences. Image ghosting is well within the manufacturer specifications (<2.5%) and no RF noise is visible. Maximum sensitivity of the PET insert is 11.0% at the center of the FOV even with simultaneous acquisition of EPI and RARE. PET MLEM resolution is 0.87 mm (FWHM) at 5 mm off-center of the FOV and 0.97 mm at 25 mm radial offset. The peaks for true/noise equivalent count rates are 410/240 and 628/486 kcps for the rat and mouse phantoms, and are reached at 30.34/22.85 and 27.94/22.58 MBq. PET image quality is minimally altered by the different MRI sequences. The Bruker PET insert shows no adverse effect on the MRI performance and demonstrated a high sensitivity, sub-millimeter resolution and good image quality even during simultaneous MRI acquisition.