Phantom evaluation of electrical conductivity mapping by MRI: Comparison to vector network analyzer measurements and spatial resolution assessment.

PURPOSE: To evaluate the performance of various MR electrical properties tomography (MR-EPT) methods at 3 T in terms of absolute quantification and spatial resolution limit for electrical conductivity. METHODS: Absolute quantification as well as spatial resolution performance were evaluated on homogeneous phantoms and a phantom with holes of different sizes, respectively. Ground-truth conductivities were measured with an open-ended coaxial probe connected to a vector network analyzer (VNA). Four widely used MR-EPT reconstruction methods were investigated: phase-based Helmholtz (PB), phase-based convection-reaction (PB-cr), image-based (IB), and generalized-image-based (GIB). These methods were compared using the same complex images from a 1 mm-isotropic UTE sequence. Alternative transceive phase acquisition sequences were also compared in PB and PB-cr. RESULTS: In large homogeneous phantoms, all methods showed a strong correlation with ground truth conductivities (r > 0.99); however, GIB was the best in terms of accuracy, spatial uniformity, and robustness to boundary artifacts. In the resolution phantom, the normalized root-mean-squared error of all methods grew rapidly (>0.40) when the hole size was below 10 mm, with simplified methods (PB and IB), or below 5 mm, with generalized methods (PB-cr and GIB). CONCLUSION: VNA measurements are essential to assess the accuracy of MR-EPT. In this study, all tested MR-EPT methods correlated strongly with the VNA measurements. The UTE sequence is recommended for MR-EPT, with the GIB method providing good accuracy for structures down to 5 mm. Structures below 5 mm may still be detected in the conductivity maps, but with significantly lower accuracy.

Body Surface Gastrointestinal Potential Mapping: A Simulation Framework to Evaluate Source Separation Algorithms.

Gastrointestinal (GI) potential mapping could be useful for evaluating GI motility disorders. Such disorders are found in inflammatory bowel diseases, such as Crohn's disease, or GI functional disorders. GI potential mapping data originate from a mixture of several GI electrophysiological sources (termed ExG) and other noise sources, including the electrocardiogram (ECG) and respiration. Denoising and/or source separation techniques are required, however, with real measurements, no ground truth is available. In this paper we propose a framework for the simulation of body surface GI potential mapping data. The framework is an electrostatic model, based on fecgsyn toolbox, using dipoles as electrical sources for the heart, stomach, small bowel and colon, and an array of surface electrodes. It is shown to generate realistic ExG waveforms, which are then used to compare several ECG and respiration cancellation techniques, based on, fast independent component analysis (FastICA) and pseudo-periodic component analysis (PiCA). The best performance was obtained with PiCA with a median root mean squared error of 0.005.

An Adaptative Savitzky-Golay Kernel for Laplacian Estimation in Magnetic Resonance Electrical Property Tomography.

Magnetic Resonance electrical property tomography (MR-EPT) is a non-invasive imaging modality that reconstructs the living biological tissue's conductivity σ and εr permittivity using spatial derivatives of the measured RF field, also termed B1 data, in a magnetic resonance imaging system. The spatial derivative operator, particularly the Laplacian, amplifies the noise in the reconstructed electrical property (EP) maps, hence decreasing accuracy and increasing boundary artifacts. We propose a novel adaptative convolution kernel for generating numerical derivatives based on 3D Savitzky-Golay (SG) filters and local segmentation in a magnitude image. In comparison to typical SG kernel, the proposed kernel allows arbitrary shapes and sizes to vary with local tissue. It provides an automatic trade-off between noise and resolution, thereby significantly enhancing reconstruction accuracy and eliminating boundary artifacts.

A Generative Adversarial Network to Synthesize 3D Magnetohydrodynamic Distortions for Electrocardiogram Analyses Applied to Cardiac Magnetic Resonance Imaging.

Recently, deep learning (DL) models have been increasingly adopted for automatic analyses of medical data, including electrocardiograms (ECGs). Large, available ECG datasets, generally of high quality, often lack specific distortions, which could be helpful for enhancing DL-based algorithms. Synthetic ECG datasets could overcome this limitation. A generative adversarial network (GAN) was used to synthesize realistic 3D magnetohydrodynamic (MHD) distortion templates, as observed during magnetic resonance imaging (MRI), and then added to available ECG recordings to produce an augmented dataset. Similarity metrics, as well as the accuracy of a DL-based R-peak detector trained with and without data augmentation, were used to evaluate the effectiveness of the synthesized data. Three-dimensional MHD distortions produced by the proposed GAN were similar to the measured ones used as input. The precision of a DL-based R-peak detector, tested on actual unseen data, was significantly enhanced by data augmentation; its recall was higher when trained with augmented data. Using synthesized MHD-distorted ECGs significantly improves the accuracy of a DL-based R-peak detector, with a good generalization capacity. This provides a simple and effective alternative to collecting new patient data. DL-based algorithms for ECG analyses can suffer from bias or gaps in training datasets. Using a GAN to synthesize new data, as well as metrics to evaluate its performance, can overcome the scarcity issue of data availability.

Super-Resolved Dynamic 3D Reconstruction of the Vocal Tract during Natural Speech.

MRI is the gold standard modality for speech imaging. However, it remains relatively slow, which complicates imaging of fast movements. Thus, an MRI of the vocal tract is often performed in 2D. While 3D MRI provides more information, the quality of such images is often insufficient. The goal of this study was to test the applicability of super-resolution algorithms for dynamic vocal tract MRI. In total, 25 sagittal slices of 8 mm with an in-plane resolution of 1.6 × 1.6 mm2 were acquired consecutively using a highly-undersampled radial 2D FLASH sequence. The volunteers were reading a text in French with two different protocols. The slices were aligned using the simultaneously recorded sound. The super-resolution strategy was used to reconstruct 1.6 × 1.6 × 1.6 mm3 isotropic volumes. The resulting images were less sharp than the native 2D images but demonstrated a higher signal-to-noise ratio. It was also shown that the super-resolution allows for eliminating inconsistencies leading to regular transitions between the slices. Additionally, it was demonstrated that using visual stimuli and shorter text fragments improves the inter-slice consistency and the super-resolved image sharpness. Therefore, with a correct speech task choice, the proposed method allows for the reconstruction of high-quality dynamic 3D volumes of the vocal tract during natural speech.

Feasibility of online non-rigid motion correction for high-resolution supine breast MRI.

PURPOSE: Conventional breast MRI is performed in the prone position with a dedicated coil. This allows high-resolution images without breast motion, but the patient position is inconsistent with that of other breast imaging modalities or interventions. Supine breast MRI may be an interesting alternative, but respiratory motion becomes an issue. Motion correction methods have typically been performed offline, for instance, the corrected images were not directly accessible from the scanner console. In this work, we seek to show the feasibility of a fast, online, motion-corrected reconstruction integrated into the clinical workflow. METHODS: Fully sampled T2 -weighted (T2 w) and accelerated T1 -weighted (T1 w) breast supine MR images were acquired during free-breathing and were reconstructed using a non-rigid motion correction technique (generalized reconstruction by inversion of coupled systems). Online reconstruction was implemented using a dedicated system combining the MR raw data and respiratory signals from an external motion sensor. Reconstruction parameters were optimized on a parallel computing platform, and image quality was assessed by objective metrics and by radiologist scoring. RESULTS: Online reconstruction time was 2 to 2.5 min. The metrics and the scores related to the motion artifacts significantly improved for both T2 w and T1 w sequences. The overall quality of T2 w images was approaching that of the prone images, whereas the quality of T1 w images remained significantly lower. CONCLUSION: The proposed online algorithm allows a noticeable reduction of motion artifacts and an improvement of the diagnostic quality for supine breast imaging with a clinically acceptable reconstruction time. These findings serve as a starting point for further development aimed at improving the quality of T1 w images.

Evaluation of Image Quality of Motion-Corrected Supine Breast MRI.

Breast MRI is the most performant modality for breast cancer diagnosis and could be widespread in the future. The gold standard breast MRI is performed in the prone position, but comfort and correlation with surgery or biopsy positioning can be problematic, while supine MRI could be an interesting alternative. In this work, we evaluated the image quality of T2-weighted supine breast MRI in healthy volunteers after online correction of respiratory motion artifacts compared to standard vendor's reconstruction and to standard prone MRI. T2-weighted images were acquired in the prone and free-breathing supine position in 10 volunteers. Two types of reconstructions were evaluated for supine acquisitions: the standard vendor's reconstruction and an online version of a nonrigid motion correction technique (generalized reconstruction by inversion of coupled system). Image quality criteria, including overall quality, sharpness, uniformity, and different types of artifacts, were assessed and scored by 2 radiologists in a randomized fashion. Interobserver agreement was verified by Weighted Cohen's Kappa calculation and a comparison between the different acquisitions was made by Wilcoxon signed-rank test. Generalized Reconstruction by Inversion of Coupled Systems (GRICS) reconstruction method significantly increased image quality in comparison to the standard reconstruction of supine acquisition. It allows a comparable quality, slightly lower than the gold standard prone MRI in T2-weighted images but it needs to be assessed with more patients and with target lesions before it can be used in clinical practice.

A Deep Learning Architecture Using 3D Vectorcardiogram to Detect R-Peaks in ECG with Enhanced Precision.

Providing reliable detection of QRS complexes is key in automated analyses of electrocardiograms (ECG). Accurate and timely R-peak detections provide a basis for ECG-based diagnoses and to synchronize radiologic, electrophysiologic, or other medical devices. Compared with classical algorithms, deep learning (DL) architectures have demonstrated superior accuracy and high generalization capacity. Furthermore, they can be embedded on edge devices for real-time inference. 3D vectorcardiograms (VCG) provide a unifying framework for detecting R-peaks regardless of the acquisition strategy or number of ECG leads. In this article, a DL architecture was demonstrated to provide enhanced precision when trained and applied on 3D VCG, with no pre-processing nor post-processing steps. Experiments were conducted on four different public databases. Using the proposed approach, high F1-scores of 99.80% and 99.64% were achieved in leave-one-out cross-validation and cross-database validation protocols, respectively. False detections, measured by a precision of 99.88% or more, were significantly reduced compared with recent state-of-the-art methods tested on the same databases, without penalty in the number of missed peaks, measured by a recall of 99.39% or more. This approach can provide new applications for devices where precision, or positive predictive value, is essential, for instance cardiac magnetic resonance imaging.

New magnetic resonance imaging sequences for fibrosis assessment in Crohn's disease: a pilot study.

BACKGROUND AND OBJECTIVE: Patients with Crohn's disease can develop intestinal strictures, containing various degrees of inflammation and fibrosis. Differentiation of the main component of a structuring lesion is the key for defining the therapeutic management. We evaluated new magnetic resonance imaging sequences (IVIM (Intravoxel Incoherent Motion imaging) and T1 mapping) for assessing fibrosis in Crohn's disease. METHODS: This was a prospective, single-center study of adult patients with Crohn's disease and magnetic resonance imaging examination, including IVIM and T1 mapping sequences, between March 2021 and April 2021. The association between the perfusion fraction (IVIM), reduction of relaxation time between pre- and postcontrast enhancement (T1 mapping), and the degree of fibrosis assessed by a visual analog scale from 0 to 10 was evaluated. RESULTS: A total of 33 patients were included. The perfusion fraction was significantly correlated with fibrosis, with lower perfusion fraction in severe fibrosis (p = .002). T1 mapping sequence was also correlated with the degree of fibrosis, reduction of relaxation time was higher in patients with severe fibrosis than in patients with mild fibrosis (p = .05). CONCLUSION: In Crohn's disease, these new tools could improve the performance of magnetic resonance imaging for transmural fibrosis quantification, and may be useful for improving care.

A hardware and software system for MRI applications requiring external device data.

PURPOSE: Numerous MRI applications require data from external devices. Such devices are often independent of the MRI system, so synchronizing these data with the MRI data is often tedious and limited to offline use. In this work, a hardware and software system is proposed for acquiring data from external devices during MR imaging, for use online (in real-time) or offline. METHODS: The hardware includes a set of external devices - electrocardiography (ECG) devices, respiration sensors, microphone, electronics of the MR system etc. - using various channels for data transmission (analog, digital, optical fibers), all connected to a server through a universal serial bus (USB) hub. The software is based on a flexible client-server architecture, allowing real-time processing pipelines to be configured and executed. Communication protocols and data formats are proposed, in particular for transferring the external device data to an open-source reconstruction software (Gadgetron), for online image reconstruction using external physiological data. The system performance is evaluated in terms of accuracy of the recorded signals and delays involved in the real-time processing tasks. Its flexibility is shown with various applications. RESULTS: The real-time system had low delays and jitters (on the order of 1 ms). Example MRI applications using external devices included: prospectively gated cardiac cine imaging, multi-modal acquisition of the vocal tract (image, sound, and respiration) and online image reconstruction with nonrigid motion correction. CONCLUSION: The performance of the system and its versatile architecture make it suitable for a wide range of MRI applications requiring online or offline use of external device data.

In Vivo Super-Resolution Cardiac Diffusion Tensor MRI: A Feasibility Study.

A super-resolution (SR) technique is proposed for imaging myocardial fiber architecture with cardiac magnetic resonance. Images were acquired with a motion-compensated cardiac diffusion tensor imaging (cDTI) sequence. The heart left ventricle was covered with three stacks of thick slices, in short axis, horizontal and vertical long axes orientations, respectively. The three low-resolution stacks (2 × 2 × 8 mm3) were combined into an isotropic volume (2 × 2 × 2 mm3) by a super-resolution reconstruction. For in vivo measurements, each slice was acquired during a breath-hold period. Bulk motion was corrected by optimizing a similarity metric between intensity profiles from all intersecting slices in the dataset. The benefit of the proposed approach was evaluated using a numerical heart phantom, a physical helicoidal phantom with artificial fibers, and six healthy subjects. The SR technique showed improved results compared to the native scans, in terms of image quality and cDTI metrics. In particular, the myocardial helix angle (HA) was more accurately estimated in the physical phantom (HA = 41.5° ± 1.1°, with the ground truth being 42.0°). In vivo, it resulted in a sharper rate of change of HA across the myocardial wall (-0.993°/% ± 0.007°/% against -0.873°/% ± 0.010°/%).

Magnetic Resonance Elastography for Assessing Fibrosis in Patients with Crohn's Disease: A Pilot Study.

BACKGROUND: Patients with Crohn's disease can develop intestinal strictures, containing various degrees of inflammation and fibrosis. Differentiation of the main component of a stricturing lesion is the key for defining the therapeutic management. AIMS: We assessed for the first time the accuracy of magnetic resonance elastography in detecting intestinal fibrosis and predicting clinical course in patients with Crohn's disease. METHODS: This was a prospective study of adult patients with Crohn's disease and magnetic resonance imaging examination, including magnetic resonance elastography, between April 2019 and February 2020. The association between the bowel stiffness value and the degree of fibrosis was evaluated. The relationship between the stiffness value and the occurrence of clinical events was also investigated. RESULTS: A total of 69 patients were included. The stiffness value measured by magnetic resonance elastography was correlated with the degree of fibrosis (p < 0.001). A bowel stiffness ≥ 3.57 kPa predicted the occurrence of clinical events with an area under the curve of 0.82 (95% CI 0.71-0.93). Bowel stiffness ≥ 3.57 kPa was associated with an increased risk of clinical events (p < 0.0001). CONCLUSION: In Crohn's disease, magnetic resonance elastography is a reliable tool for detecting intestinal fibrosis and predicting a worse disease outcome.

Fully digital PET is unaffected by any deterioration in TOF resolution and TOF image quality in the wide range of routine PET count rates.

PURPOSE: Digital PET involving silicon photomultipliers (SiPM) provides an enhanced time-of-flight (TOF) resolution as compared with photomultiplier (PMT)-based PET, but also a better prevention of the count-related rises in dead time and pile-up effects mainly due to smaller trigger domains (i.e., the detection surfaces associated with each trigger circuit). This study aimed to determine whether this latter property could help prevent against deteriorations in TOF resolution and TOF image quality in the wide range of PET count rates documented in clinical routine. METHODS: Variations, according to count rates, in timing resolution and in TOF-related enhancement of the quality of phantom images were compared between the first fully digital PET (Vereos) and a PMT-based PET (Ingenuity). Single-count rate values were additionally extracted from the list-mode data of routine analog- and digital-PET exams at each 500-ms interval, in order to determine the ranges of routine PET count rates. RESULTS: Routine PET count rates were lower for the Vereos than for the Ingenuity. For Ingenuity, the upper limits were estimated at approximately 21.7 and 33.2 Mcps after injection of respectively 3 and 5 MBq.kg-1 of current 18F-labeled tracers. At 5.8 Mcps, corresponding to the lower limit of the routine count rates documented with the Ingenuity, timing resolutions provided by the scatter phantom were 326 and 621 ps for Vereos and Ingenuity, respectively. At higher count rates, timing resolution was remarkably stable for Vereos but exhibited a progressive deterioration for Ingenuity, respectively reaching 732 and 847 ps at the upper limits of 21.7 and 33.2 Mcps. The averaged TOF-related gain in signal/noise ratio was stable at approximately 2 for Vereos but decreased from 1.36 at 5.8 Mcps to 1.14 and 1.00 at respectively 21.7 and 33.2 Mcps for Ingenuity. CONCLUSION: Contrary to the Ingenuity PMT-based PET, the Vereos fully digital PET is unaffected by any deterioration in TOF resolution and consequently, in the quality of TOF images, in the wide range of routine PET count rates. This advantage is even more striking with higher count-rates for which the preferential use of digital PET should be further recommended (i.e., dynamic PET recording, higher injected activities).

MR electrical properties imaging using a generalized image-based method.

PURPOSE: To develop a fast and easy-to-use electrical properties tomography (EPT) method based on a single MR scan, avoiding both the need of a B1 -map and transceive phase assumption, and that is robust against noise. THEORY: Derived from Maxwell's equations, conductivity, and permittivity are reconstructed from a new partial differential equation involving the product of the RF fields and its derivatives. This also allows us to clarify and revisit the relevance of common assumptions of MREPT. METHODS: Our new governing equation is solved using a 3D finite-difference scheme and compared to previous frameworks. The benefits of our method over selected existing MREPT methods are demonstrated for different simulation models, as well as for both an inhomogeneous agar phantom gel and in vivo brain data at 3T. RESULTS: Simulation and experimental results are illustrated to highlight the merits of the proposed method over existing methods. We show the validity of our algorithm in versatile configurations, with many transition regions notably. Complex admittivity maps are also provided as a complementary MR contrast. CONCLUSION: Because it avoids time-consuming RF field mapping and generalizes the use of standard MR image for electrical properties reconstruction, this contribution is promising as a new step forward for clinical applications.

Plasma Galectin-3 predicts deleterious vascular dysfunction affecting post-myocardial infarction patients: An explanatory study.

OBJECTIVES: In a previous analysis of a post-myocardial infarction (MI) cohort, abnormally high systemic vascular resistances (SVR) were shown to be frequently revealed by MRI during the healing period, independently of MI severity, giving evidence of vascular dysfunction and limiting further recovery of cardiac function. The present ancillary and exploratory analysis of the same cohort was aimed at characterizing those patients suffering from high SVR remotely from MI with a large a panel of cardiovascular MRI parameters and blood biomarkers. METHODS: MRI and blood sampling were performed 2-4 days after a reperfused MI and 6 months thereafter in 121 patients. SVR were monitored with a phase-contrast MRI sequence and patients with abnormally high SVR at 6-months were characterized through MRI parameters and blood biomarkers, including Galectin-3, an indicator of cardiovascular inflammation and fibrosis after MI. SVR were normal at 6-months in 90 patients (SVR-) and abnormally high in 31 among whom 21 already had high SVR at the acute phase (SVR++) while 10 did not (SVR+). RESULTS: When compared with SVR-, both SVR+ and SVR++ exhibited lower recovery in cardiac function from baseline to 6-months, while baseline levels of Galectin-3 were significantly different in both SVR+ (median: 14.4 (interquartile range: 12.3-16.7) ng.mL-1) and SVR++ (13.0 (11.7-19.4) ng.mL-1) compared to SVR- (11.7 (9.8-13.5) ng.mL-1, both p < 0.05). Plasma Galectin-3 was an independent baseline predictor of high SVR at 6-months (p = 0.002), together with the baseline levels of SVR and left ventricular end-diastolic volume, whereas indices of MI severity and left ventricular function were not. In conclusion, plasma Galectin-3 predicts a deleterious vascular dysfunction affecting post-MI patients, an observation that could lead to consider new therapeutic targets if confirmed through dedicated prospective studies.

Monte Carlo simulation of digital photon counting PET.

A GATE Monte Carlo model of the Philips Vereos digital photon counting PET imaging system using silicon photo-multiplier detectors was proposed. It was evaluated against experimental data in accordance with NEMA guidelines. Comparisons were performed using listmode data in order to remain independent of image reconstruction algorithms. An original line of response-based method is proposed to estimate intrinsic spatial resolution without reconstruction. Four sets of experiments were performed: (1) count rates and scatter fraction, (2) energy and timing resolutions, (3) sensitivity, and (4) intrinsic spatial resolution. Experimental and simulated data were found to be in good agreement, with overall differences lower than 10% for activity concentrations used in most standard clinical applications. Illustrative image reconstructions were provided. In conclusion, the proposed Monte Carlo model was validated and can be used for numerous studies such as optimizing acquisition parameters or reconstruction algorithms.

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising.

PURPOSE: To accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a post-processing 3D denoising technique to maintain high accuracy and precision. METHODS: 3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and low standard deviation (as a surrogate for precision) is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Following the results from the healthy subjects, three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising. RESULTS: In the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P = 0.99 and P = 0.99 for accuracy, P = 0.64 and P = 0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1-weighted images after denoising. CONCLUSION: We demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.

Broadband electrocardiogram acquisition for improved suppression of MRI gradient artifacts.

OBJECTIVE: Despite being routinely acquired during MRI examinations for triggering or monitoring purposes, electrocardiogram (ECG) signal recording and analysis remain challenging due to the inherent magnetic environment of an MRI scanner. The ECG signals are particularly distorted by the induction of electrical fields in the body by the MRI gradients. In this study, we propose a new hardware and software solution for the acquisition of ECG signal during MRI up to 3 T. APPROACH: Instead of restricting the sensor bandwidth to limit these gradient artifacts, the new sensor architecture has a higher bandwidth, higher sampling frequency and larger input dynamics, in order to acquire the ECG signals and the gradient artifacts more precisely. Signal processing based on a novel detection algorithm and blanking are then applied for improved artifact suppression. MAIN RESULTS: The proposed sensor allows the gradient artifacts to be acquired more precisely, and these artifacts are recorded with peak-to-peak amplitudes two orders of magnitude larger than for QRS complexes. The proposed method outperforms a state-of-the-art approach both in terms of signal quality (+9% 'SNR') and accuracy of QRS detection (+11%). SIGNIFICANCE: The proposed hardware and software solutions open the way for the acquisition of high-quality of ECG gating in MRI, and improved diagnostic quality of ECG signals in MRI.

Head-to-head comparison between digital and analog PET of human and phantom images when optimized for maximizing the signal-to-noise ratio from small lesions.

BACKGROUND: Routine PET exams are increasingly performed with reduced injected activities, leading to the use of different image reconstruction parameters than the NEMA parameters, in order to prevent from any deleterious decrease in signal-to-noise ratio (SNR) and thus, in lesion detectability. This study aimed to provide a global head-to-head comparison between digital (Vereos, Philips®) and analog (Ingenuity TF, Philips®) PET cameras of the trade-off between SNR and contrast through a wide-ranging number of reconstruction iterations, and with a further reconstruction optimization based on the SNR of small lesions. METHODS: Image quality parameters were compared between the two cameras on human and phantom images for a number of OSEM reconstruction iterations ranging from 1 to 10, the number of subsets being fixed at 10, and with the further identification of reconstruction parameters maximizing the SNR of spheres and adenopathies nearing 10 mm in diameter. These reconstructions were additionally obtained with and without time-of-flight (TOF) information (TOF and noTOF images, respectively) for further comparisons. RESULTS: On both human and phantom TOF images, the compromise between SNR and contrast was consistently more advantageous for digital than analog PET, with the difference being particularly pronounced for the lowest numbers of iterations and the smallest spheres. SNR was maximized with 1 and 2 OSEM iterations for the TOF images from digital and analog PET, respectively, whereas 4 OSEM iterations were required for the corresponding noTOF images from both cameras. On the TOF images obtained with this SNR optimization, digital PET exhibited a 37% to 44% higher SNR as compared with analog PET, depending on sphere size. These relative differences were however much lower for the noTOF images optimized for SNR (- 4 to + 18%), as well as for images reconstructed according to NEMA standards (- 4 to + 12%). CONCLUSION: SNR may be dramatically higher for digital PET than for analog PET, especially when optimized for small lesions. This superiority is mostly attributable to enhanced TOF resolution and is significantly underestimated in NEMA-based analyses.