Increased Acquisition Time Research Articles

Robust, fast and accurate mapping of diffusional mean kurtosis

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Robust, fast and accurate mapping of diffusional mean kurtosis.

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Dynamic MRI interpolation in temporal direction using an unsupervised generative model

PurposeCardiac cine magnetic resonance imaging (MRI) is an important tool in assessing dynamic heart function. However, this technique requires long acquisition time and long breath holds, which presents difficulties. The aim of this study is to propose an unsupervised neural network framework that can perform cardiac cine interpolation in time, so that we can increase the temporal resolution of cardiac cine without increasing acquisition time. MethodsIn this study, a subject-specific unsupervised generative neural network is designed to perform temporal interpolation for cardiac cine MRI. The network takes in a 2D latent vector in which each element corresponds to one cardiac phase in the cardiac cycle and then the network outputs the cardiac cine images which are acquired on the scanner. After the training of the generative network, we can interpolate the 2D latent vector and input the interpolated latent vector into the network and the network will output the frame-interpolated cine images. The results of the proposed cine interpolation neural network (CINN) framework are compared quantitatively and qualitatively with other state-of-the-art methods, the ground truth training cine frames, and the ground truth frames removed from the original acquisition. Signal-to-noise ratio (SNR), structural similarity index measures (SSIM), peak signal-to-noise ratio (PSNR), strain analysis, as well as the sharpness calculated using the Tenengrad algorithm were used for image quality assessment. ResultsAs shown quantitatively and qualitatively, the proposed framework learns the generative task well and hence performs the temporal interpolation task well. Furthermore, both quantitative and qualitative comparison studies show the effectiveness of the proposed framework in cardiac cine interpolation in time. ConclusionThe proposed generative model can effectively learn the generative task and perform high quality cardiac cine interpolation in time.

Dynamic Ultrasound Localization Microscopy Without ECG-Gating

ObjectiveDynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration. MethodsWe developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time. ResultsInitially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated. ConclusionResults suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.

Improved MRI methods to quantify retinal and choroidal blood flow applied to a model of glaucoma.

Blood flow (BF) of the retinal and choroidal vasculatures can be quantitatively imaged using MRI. This study sought to improve methods of data acquisition and analysis for MRI of layer-specific retinal and choroidal BF and then applied this approach to detect reduced ocular BF in a well-established mouse model of glaucoma from both eyes. Quantitative BF magnetic resonance imaging (MRI) was performed on glaucomatous DBA/2J and normal C57BL/6J mice. Arterial spin labeling MRI was applied to image retinal and choroidal BF using custom-made dual eye coils that could image both eyes during the same scan. Statistics using data from a single eye or two eyes were compared. BF values were calculated using two approaches. The BF rate per quantity of tissue was calculated as commonly done, and the peak BF values of the retinal and choroidal vasculatures were taken. Additionally, the BF rate per retinal surface area was calculated using a new analysis approach to attempt to reduce partial volume and variability by integrating BF over the retinal and choroidal depths. Ocular BF of both eyes could be imaged using the dual coil setup without effecting scan time. Intraocular pressure was significantly elevated in DBA/2J mice compared to C57BL/6J mice (P<0.01). Both retinal and choroidal BF were significantly decreased in DBA/2J mice in comparison to the age-matched normal C57BL/6J mice across all measurements (P < 0.01). From simulations, the values from the integrated BF analysis method had less partial volume effect, and from in vivo scans, this analysis approach also improved power. The dual eye coil setup allows bilateral eye data acquisition, increasing the amount of data acquired without increasing acquisition times in vivo. The reduced ocular BF found using the improved acquisition and analysis approaches replicated the results of previous studies on DBA/2J mice. The ocular hypertensive stress-induced BF reduction found within these mice may represent changes associated with glaucomatous progression.

New full-counts phase-matched data-driven gated (DDG) PET/CT.

Data-driven gated (DDG) PET has gained clinical acceptance and has been shown to match or outperform external-device gated (EDG) PET. However, in most clinical applications, DDG PET is matched with helical CT acquired in free breathing (FB) at a random respiratory phase, leaving registration, and optimal attenuation correction (AC) to chance. Furthermore, DDG PET requires additional scan time to reduce image noise as it only preserves 35%-50% of the PET data at or near the end-expiratory phase of the breathing cycle. A new full-counts, phase-matched (FCPM) DDG PET/CT was developed based on a low-dose cine CT to improve registration between DDG PET and DDG CT, to reduce image noise, and to avoid increasing acquisition times in DDG PET. A new DDG CT was developed for three respiratory phases of CT images from a low dose cine CT acquisition of 1.35mSv for a coverage of about 15.4cm: end-inspiration (EI), average (AVG), and end-expiration (EE) to match with the three corresponding phases of DDG PET data: -10% to 15%; 15% to 30%, and 80% to 90%; and 30% to 80%, respectively. The EI and EE phases of DDG CT were selected based on the physiological changes in lung density and body outlines reflected in the dynamic cine CT images. The AVG phase was derived from averaging of all phases of the cine CT images. The cine CT was acquired over the lower lungs and/or upper abdomen for correction of misregistration between PET and FB CT as well as DDG PET and FB CT. The three phases of DDG CT were used for AC of the corresponding phases of PET. After phase-matched AC of each PET dataset, the EI and AVG PET data were registered to the EE PET data with deformable image registration. The final result was FCPM DDG PET/CT which accounts for all PET data registered at the EE phase. We applied this approach to 14 18F-FDG lung cancer patient studies acquired at 2min/bed position on the GE Discovery MI (25-cm axial FOV) and evaluated its efficacy in improved quantification and noise reduction. Relative to static PET/CT, the SUVmax increases for the EI, AVG, EE, and FCPM DDG PET/CT were 1.67±0.40, 1.50±0.28, 1.64±0.36, and 1.49±0.28, respectively. There were 10.8% and 9.1% average decreases in SUVmax from EI and EE to FCPM DDG PET/CT, respectively. EI, AVG, and EE DDG PET/CT all maintained increased image noise relative to static PET/CT. However, the noise levels of FCPM and static PET were statistically equivalent, suggesting the inclusion of all counts was able to decrease the image noise relative to EI and EE DDG PET/CT. A new FCPM DDG PET/CT has been developed to account for 100% of collected PET data in DDG PET applications. Image noise in FCPM is comparable to static PET, while small decreases in SUVmax were also observed in FCPM when compared to either EI or EE DDG PET/CT.

High-speed fluorescence excitation-scanning hyperspectral imaging microscopy using thin-film tunable filters.

Hyperspectral imaging (HSI) technologies have enabled a range of experimental techniques and studies in the fluorescence microscopy field. Unfortunately, a drawback of many HSI microscope platforms is increased acquisition time required to collect images across many spectral bands, as well as signal loss due to the need to filter or disperse emitted fluorescence into many discrete bands. We have previously demonstrated that an alternative approach of scanning the fluorescence excitation spectrum can greatly improve system efficiency by decreasing light losses associated with emission filtering. Our initial system was configured using an array of thin-film tunable filters (TFTFs, VersaChrome, Semrock) mounted in a tiltable filter wheel (VF-5, Sutter) that required ~150-200 ms to switch between wavelengths. Here, we present a new configuration for high-speed switching of TFTFs to allow rapid time-lapse HSI microscopy. A TFTF array was mounted in a custom holder that was attached to a piezoelectric rotation mount (ThorLabs), allowing high-speed rotation. Switching between adjacent filters was achieved using the internal optics of a DG-4 lightsource (Sutter Instrument), including a pair of off-axis parabolic mirrors and galvanometers. Output light was coupled to a liquid lightguide and into an inverted widefield fluorescence microscope (TI-2, Nikon Instruments). Initial tests indicate that the HSI system provides a 15-20 nm bandwidth tunable excitation band and ~10-20 ms wavelength switch time, allowing for high-speed HSI imaging of dynamic cellular events. This work was supported by NIH P01HL066299, R01HL169522, NIH TL1TR003106, and NSF MRI1725937.

Potential Clinical Impact of LAFOV PET/CT: A Systematic Evaluation of Image Quality and Lesion Detection.

We performed a systematic evaluation of the diagnostic performance of LAFOV PET/CT with increasing acquisition time. The first 100 oncologic adult patients referred for 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose PET/CT on the Siemens Biograph Vision Quadra were included. A standard imaging protocol of 10 min was used and scans were reconstructed at 30 s, 60 s, 90 s, 180 s, 300 s, and 600 s. Paired comparisons of quantitative image noise, qualitative image quality, lesion detection, and lesion classification were performed. Image noise (n = 50, 34 women) was acceptable according to the current standard of care (coefficient-of-varianceref < 0.15) after 90 s and improved significantly with increasing acquisition time (PB < 0.001). The same was seen in observer rankings (PB < 0.001). Lesion detection (n = 100, 74 women) improved significantly from 30 s to 90 s (PB < 0.001), 90 s to 180 s (PB = 0.001), and 90 s to 300 s (PB = 0.002), while lesion classification improved from 90 s to 180 s (PB < 0.001), 180 s to 300 s (PB = 0.021), and 90 s to 300 s (PB < 0.001). We observed improved image quality, lesion detection, and lesion classification with increasing acquisition time while maintaining a total scan time of less than 5 min, which demonstrates a potential clinical benefit. Based on these results we recommend a standard imaging acquisition protocol for LAFOV PET/CT of minimum 180 s to maximum 300 s after injection of 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose.

Maximized Spatial Information and Minimized Acquisition Time of Top-Hat IR-MALDESI-MSI of Zebrafish Using Nested Regions of Interest (nROIs).

Increasing the spatial resolution of a mass spectrometry imaging (MSI) method results in a more defined heatmap of the spatial distribution of molecules across a sample, but it is also associated with the disadvantage of increased acquisition time. Decreasing the area of the region of interest to achieve shorter durations results in the loss of potentially valuable information in larger specimens. This work presents a novel MSI method to reduce the time of MSI data acquisition with variable step size imaging: nested regions of interest (nROIs). Using nROIs, a small ROI may be imaged at a higher spatial resolution while nested inside a lower-spatial-resolution peripheral ROI. This conserves the maximal spatial and chemical information generated from target regions while also decreasing the necessary acquisition time. In this work, the nROI method was characterized on mouse liver and applied to top-hat MSI of zebrafish using a novel optical train, which resulted in a significant improvement in both acquisition time and spatial detail of the zebrafish. The nROI method can be employed with any step size pairing and adapted to any method in which the acquisition time of larger high-resolution ROIs poses a practical challenge.

Feasibility of 4D HDR brachytherapy source tracking using x-ray tomosynthesis: Monte Carlo investigation.

High dose rate (HDR) brachytherapy rapidly delivers dose to targets with steep dose gradients. This treatment method must adhere to prescribed treatment plans with high spatiotemporal accuracy and precision, as failure to do so may degrade clinical outcomes. One approach to achieving this goal is to develop imaging techniques to track HDR sources in vivo in reference to surrounding anatomy. This work investigates the feasibility of using an isocentric C-arm x-ray imager and tomosynthesis methods to track Ir-192 HDR brachytherapy sources in vivo over time (4D). A tomosynthesis imaging workflow was proposed and its achievable source detectability, localization accuracy, and spatiotemporal resolution were investigated in silico. An anthropomorphic female XCAT phantom was modified to include a vaginal cylinder applicator and Ir-192 HDR source (0.5 × 0.5 × 5.0 mm3 ), and the workflow was carried out using the MC-GPU Monte Carlo image simulation platform. Source detectability was characterized using the reconstructed source signal-difference-to-noise-ratio (SDNR), localization accuracy by the absolute 3D error in its measured centroid location, and spatiotemporal resolution by the full-width-at-half-maximum (FWHM) of line profiles through the source in each spatial dimension considering a maximum C-arm angular velocity of 30° per second. The dependence of these parameters on acquisition angular range (θtot = 0°-90°), number of views, angular increment between views (Δθ = 0°-15°), and volumetric constraints imposed in reconstruction was evaluated. Organ voxel doses were tallied to derive the workflow's attributable effective dose. The HDR source was readily detected and its centroid was accurately localized with the proposed workflow and method (SDNR: 10-40, 3D error: 0-0.144 mm). Tradeoffs were demonstrated for various combinations of image acquisition parameters; namely, increasing the tomosynthesis acquisition angular range improved resolution in the depth-encoded direction, for example from 2.5 mm to 1.2 mm between θtot = 30o and θtot = 90o , at the cost of increasing acquisition time from 1 to 3 s. The best-performing acquisition parameters (θtot = 90o , Δθ = 1°) yielded no centroid localization error, and achieved submillimeter source resolution (0.57 × 1.21 × 5.04 mm3 apparent source dimensions, FWHM). The total effective dose for the workflow was 263 µSv for its required pre-treatment imaging component and 7.59 µSv per mid-treatment acquisition thereafter, which is comparable to common diagnostic radiology exams. A system and method for tracking HDR brachytherapy sources in vivo using C-arm tomosynthesis was proposed and its performance investigated in silico. Tradeoffs in source conspicuity, localization accuracy, spatiotemporal resolution, and dose were determined. The results suggest this approach is feasible for localizing an Ir-192 HDR source in vivo with submillimeter spatial resolution, 1-3 second temporal resolution and minimal additional dose burden.

Fiber-optic hydrophone for detection of high-intensity ultrasound waves.

Fiber-optic hydrophones (FOHs) are widely used to detect high-intensity focused ultrasound (HIFU) fields. The most common type consists of an uncoated single-mode fiber with a perpendicularly cleaved end face. The main disadvantage of these hydrophones is their low signal-to-noise ratio (SNR). To increase the SNR, signal averaging is performed, but the associated increased acquisition times hinder ultrasound field scans. In this study, with a view to increasing SNR while withstanding HIFU pressures, the bare FOH paradigm is extended to include a partially reflective coating on the fiber end face. Here, a numerical model based on the general transfer-matrix method was implemented. Based on the simulation results, a single-layer, 172 nm TiO2-coated FOH was fabricated. The frequency range of the hydrophone was verified from 1 to 30 MHz. The SNR of the acoustic measurement with the coated sensor was 21 dB higher than that of the uncoated one. The coated sensor successfully withstood a peak positive pressure of 35 MPa for 6000 pulses.

Impact of Reduced Image Noise on Deauville Scores in Patients with Lymphoma Scanned on a Long-Axial Field-of-View PET/CT-Scanner

Total body and long-axial field-of-view (LAFOV) PET/CT represent visionary innovations in imaging enabling either improved image quality, reduction in injected activity-dose or decreased acquisition time. An improved image quality may affect visual scoring systems, including the Deauville score (DS), which is used for clinical assessment of patients with lymphoma. The DS compares SUVmax in residual lymphomas with liver parenchyma, and here we investigate the impact of reduced image noise on the DS in patients with lymphomas scanned on a LAFOV PET/CT. Sixty-eight patients with lymphoma underwent a whole-body scan on a Biograph Vision Quadra PET/CT-scanner, and images were evaluated visually with regard to DS for three different timeframes of 90, 300, and 600 s. SUVmax and SUVmean were calculated from liver and mediastinal blood pool, in addition to SUVmax from residual lymphomas and measures of noise. SUVmax in liver and in mediastinal blood pool decreased significantly with increasing acquisition time, whereas SUVmean remained stable. In residual tumor, SUVmax was stable during different acquisition times. As a result, the DS was subject to change in three patients. Attention should be drawn towards the eventual impact of improvements in image quality on visual scoring systems such as the DS.

Confounder-corrected T1 mapping in the liver through simultaneous estimation of T1 , PDFF, , and in a single breath-hold acquisition.

Quantitative volumetric T1 mapping in the liver has the potential to aid in the detection, diagnosis, and quantification of liver fibrosis, inflammation, and spatially resolved liver function. However, accurate measurement of hepatic T1 is confounded by the presence of fat and inhomogeneous excitation. Furthermore, scan time constraints related to respiratory motion require tradeoffs of reduced volumetric coverage and/or increased acquisition time. This work presents a novel 3D acquisition and estimation method for confounder-corrected T1 measurement over the entire liver within a single breath-hold through simultaneous estimation of T1 , fat and . The proposed method combines chemical shift encoded MRI and variable flip angle MRI with a mapping technique to enable confounder-corrected T1 mapping. The method was evaluated theoretically and demonstrated in both phantom and in vivo acquisitions at 1.5 and 3.0T. At 1.5T, the method was evaluated both pre- and post- contrast enhancement in healthy volunteers. The proposed method demonstrated excellent linear agreement with reference inversion-recovery spin-echo based T1 in phantom acquisitions at both 1.5 and 3.0T, with minimal bias (5.2 and 45 ms, respectively) over T1 ranging from 200-1200 ms. In vivo results were in general agreement with reference saturation-recovery based 2D T1 maps (SMART1 Map, GE Healthcare). The proposed 3D T1 mapping method accounts for fat and confounders through simultaneous estimation of T1 , , PDFF and . It demonstrates strong linear agreement with reference T1 measurements, with low bias and high precision, and can achieve full liver coverage in a single breath-hold.

Deep-Learning-Based Fast Optical Coherence Tomography (OCT) Image Denoising for Smart Laser Osteotomy.

Laser osteotomy promises precise cutting and minor bone tissue damage. We proposed Optical Coherence Tomography (OCT) to monitor the ablation process toward our smart laser osteotomy approach. The OCT image is helpful to identify tissue type and provide feedback for the ablation laser to avoid critical tissues such as bone marrow and nerve. Furthermore, in the implementation, the tissue classifier's accuracy is dependent on the quality of the OCT image. Therefore, image denoising plays an important role in having an accurate feedback system. A common OCT image denoising technique is the frame-averaging method. Inherent to this method is the need for multiple images, i.e., the more images used, the better the resulting image quality. However, this approach comes at the price of increased acquisition time and sensitivity to motion artifacts. To overcome these limitations, we applied a deep-learning denoising method capable of imitating the frame-averaging method. The resulting image had a similar image quality to the frame-averaging and was better than the classical digital filtering methods. We also evaluated if this method affects the tissue classifier model's accuracy that will provide feedback to the ablation laser. We found that image denoising significantly increased the accuracy of the tissue classifier. Furthermore, we observed that the classifier trained using the deep learning denoised images achieved similar accuracy to the classifier trained using frame-averaged images. The results suggest the possibility of using the deep learning method as a pre-processing step for real-time tissue classification in smart laser osteotomy.

Deep learning–based acceleration of Compressed Sense MR imaging of the ankle

ObjectivesTo evaluate a compressed sensing artificial intelligence framework (CSAI) to accelerate MRI acquisition of the ankle.MethodsThirty patients were scanned at 3T. Axial T2-w, coronal T1-w, and coronal/sagittal intermediate-w scans with fat saturation were acquired using compressed sensing only (12:44 min, CS), CSAI with an acceleration factor of 4.6–5.3 (6:45 min, CSAI2x), and CSAI with an acceleration factor of 6.9–7.7 (4:46 min, CSAI3x). Moreover, a high-resolution axial T2-w scan was obtained using CSAI with a similar scan duration compared to CS. Depiction and presence of abnormalities were graded. Signal-to-noise and contrast-to-noise were calculated. Wilcoxon signed-rank test and Cohen’s kappa were used to compare CSAI with CS sequences.ResultsThe correlation was perfect between CS and CSAI2x (κ = 1.0) and excellent for CS and CSAI3x (κ = 0.86–1.0). No significant differences were found for the depiction of structures between CS and CSAI2x and the same abnormalities were detected in both protocols. For CSAI3x the depiction was graded lower (p ≤ 0.001), though most abnormalities were also detected. For CSAI2x contrast-to-noise fluid/muscle was higher compared to CS (p ≤ 0.05), while no differences were found for other tissues. Signal-to-noise and contrast-to-noise were higher for CSAI3x compared to CS (p ≤ 0.05). The high - resolution axial T2-w sequence specifically improved the depiction of tendons and the tibial nerve (p ≤ 0.005).ConclusionsAcquisition times can be reduced by 47% using CSAI compared to CS without decreasing diagnostic image quality. Reducing acquisition times by 63% is feasible but should be reserved for specific patients. The depiction of specific structures is improved using a high-resolution axial T2-w CSAI scan.Key Points• Prospective study showed that CSAI enables reduction in acquisition times by 47% without decreasing diagnostic image quality.• Reducing acquisition times by 63% still produces images with an acceptable diagnostic accuracy but should be reserved for specific patients.• CSAI may be implemented to scan at a higher resolution compared to standard CS images without increasing acquisition times.

Two birds with one stone: can [68Ga]Ga-DOTANOC PET/CT image quality be improved through BMI-adjusted injected activity without increasing acquisition times?

To assess how patients' dependent parameters may affect [68Ga]Ga-DOTANOC image quality and to propose a theoretical body mass index (BMI)-adjusted injected activity (IA) scheme, to improve imaging of high weight patients. Among patients prospectively enrolled (June-2019 and May-2020) in an Institutional Ethical Committee-approved electronic archive, we included those affected by primary gastro-entero-pancreatic (GEP) or lung neuroendocrine tumour and referred by our Institutional clinicians (excluding even minimal radiopharmaceutical extravasation, movement artefacts, renal insufficiency). All PET/CT images were acquired following EANM guidelines and rated for visual quality (1 = non-diagnostic, 2 = poor, 3 = moderate, 4 = good). Collected data included patient's body mass, height, BMI, age, IA (injected activity), IA/Kg (IAkg), IA/BMI (IABMI), liver SUVmean, liver SUVmax standard deviation, liver-signal-to-noise (LSNR), normalised_LSNR (LSNR_norm) and contrast-to-noise ratio (CNR) for positive scans and were compared to image rating (poor vs moderate/good). Overall, 77 patients were included. Rating concordance was high (agreement = 81.8%, Fleiss k score = 0.806). All patients' dependent parameters resulted significantly different between poor-rated and moderate/good-rated scans (IA: p = 0.006, IAkg: p =< 0.001, body weight: p =< 0.001, BMI: p =< 0.001, IABMI: p =< 0.001). Factors significantly associated with moderate/good rating were BMI (p =< 0.001), body weight (p =< 0.001), IABMI (p =< 0.001), IAkg (p = 0.001), IA (p = 0.003), LSNR_norm (p = 0.01). The BMI-based model presented the best predictive efficiency (81.82%). IABMI performance to differentiate moderate/good from poor rating resulted statistically significant (IA-AUC = 0.78; 95% CI: 0.68-0.89; cut-off value of 4.17 MBq*m2/kg, sensitivity = 81.1%, specificity = 66.7%). If BMI-adjusted IA (=4.17*BMI) would have been applied in this population, the median IA would have slightly inferior (-4.8%), despite a different IA in each patient. BMI resulted the best predictor of image quality. The proposed theoretical BMI-adjusted IA scheme (4.17*BMI) should yield images of better quality (especially in high-BMI patients) maintaining practical scanning times (3 min/bed).

Higher-order multi-shell diffusion measures complement tensor metrics and volume in gray matter when predicting age and cognition

Recent advances in diffusion-weighted imaging have enabled us to probe the microstructure of even gray matter non-invasively. However, these advanced multi-shell protocols are often not included in large-scale studies as they significantly increase scan time. In this study, we investigated whether one set of multi-shell diffusion metrics commonly used in gray matter (as derived from Neurite Orientation Dispersion and Density Imaging, NODDI) provide enough additional information over typical tensor and volume metrics to justify the increased acquisition time, using the cognitive aging framework in the human hippocampus as a testbed. We first demonstrated that NODDI metrics are robust and reliable by replicating previous findings from our lab in a larger population of 79 younger (20.41 ± 1.89 years, 46 females) and 75 older (73.56 ± 6.26 years, 45 females) adults, showing that these metrics in the hippocampal subfields are sensitive to age and memory performance. We then asked how these subfield specific hippocampal NODDI metrics compared with standard tensor metrics and volume in predicting age and memory ability. We discovered that both NODDI and tensor measures separately predicted age and cognition in comparable capacities. However, integrating these modalities together considerably increased the predictive power of our logistic models, indicating that NODDI and tensor measures may be capturing independent microstructural information. We use these findings to encourage neuroimaging data collection consortiums to include a multi-shell diffusion sequence in their protocols since existing NODDI measures (and potential future multi-shell measures) may be able to capture microstructural variance that is missed by traditional approaches, even in studies exclusively examining gray matter.

High Resolution Fluorescence Lifetime Maps from Minimal Photon Counts.

Fluorescence lifetime imaging microscopy (FLIM) may reveal subcellular spatial lifetime maps of key molecular species. Yet, such a quantitative picture of life necessarily demands high photon budgets at every pixel under the current analysis paradigm, thereby increasing acquisition time and photodamage to the sample. Motivated by recent developments in computational statistics, we provide a direct means to update our knowledge of the lifetime maps of species of different lifetimes from direct photon arrivals, while accounting for experimental features such as arbitrary forms of the instrument response function (IRF) and exploiting information from empty laser pulses not resulting in photon detection. Our ability to construct lifetime maps holds for arbitrary lifetimes, from short lifetimes (comparable to the IRF) to lifetimes exceeding interpulse times. As our method is highly data efficient, for the same amount of data normally used to determine lifetimes and photon ratios, working within the Bayesian paradigm, we report direct blind unmixing of lifetimes with subnanosecond resolution and subpixel spatial resolution using standard raster scan FLIM images. We demonstrate our method using a wide range of simulated and experimental data.

A comparison between stereophotogrammetry and smartphone structured light technology for three-dimensional face scanning

To compare three-dimensional facial scans obtained by stereophotogrammetry with two different applications for smartphone supporting the TrueDepth system, a structured light technology. Facial scans of 40 different subjects were acquired with three different systems. The 3dMDtrio Stereophotogrammetry System (3dMD, Atlanta, Ga) was compared with a smartphone (iPhone Xs; Apple, Cupertino, Calif) equipped with the Bellus3D Face Application (version 1.6.11; Bellus3D Inc, Campbell, Calif) or Capture (version 1.2.5; Standard Cyborg Inc, San Francisco, Calif). Times of image acquisition and elaboration were recorded. The surface-to-surface deviation and the distance between 18 landmarks from 3dMD reference images to those acquired with Bellus3D or Capture were measured. Capturing and processing times with the smartphone applications were considerably longer than with the 3dMD system. The surface-to-surface deviation analysis between the Bellus3D and 3dMD showed an overlap percentage of 80.01% ± 5.92% and 56.62% ± 7.65% within the ranges of 1 mm and 0.5 mm discrepancy, respectively. Images from Capture showed an overlap percentage of 81.40% ± 9.59% and 56.45% ± 11.62% within the ranges of 1 mm and 0.5 mm, respectively. The face image acquisition with the 3dMD device is fast and accurate, but bulky and expensive. The new smartphone applications combined with the TrueDepth sensors show promising results. They need more accuracy from the operator and more compliance from the patient because of the increased acquisition time. Their greatest advantages are related to cost and portability.

Feasibility of ultra-high-speed acquisition in xSPECT bone algorithm: a phantom study with advanced bone SPECT-specific phantom.

Although xSPECT Bone (xB) provides quantitative single-photon emission computed tomography (SPECT) high-resolution images, patients' burden remains high due to long acquisition time; therefore, this study aimed to investigate the feasibility of shortening the xB acquisition time using a custom-designed phantom. A custom-designed xSPECT bone-specific (xSB) phantom with simulated cortical and spongious bones was developed based on the thoracic bone phantom. Both standard- and ultra-high-speed (UHS) xB acquisitions were performed in a male patient with lung cancer. In this phantom study, SPECT was acquired for 3, 6, 9, 12, and 30min. The clinical SPECT acquisition time per rotation was 9 and 3min for standard and UHS, respectively. SPECT images were reconstructed using ordered subset expectation maximization with three-dimensional resolution recovery (Flash3D; F3D) and xB algorithms. Quantitative SPECT value (QSV) and coefficient of variation (CV) were measured using the volume of interests (VOIs) placed at the center of the vertebral body and hot sphere. A linear profile was plotted on the spinous process at the center of the xSB phantom; then, the full width at half maximum (FWHM) was measured. The standardized uptake value (SUV) and standard deviation from the first thoracic to the fifth lumbar vertebrae in clinical standard- and UHS-xB images were measured using a 1-cm3 VOI. The QSV of F3D images was underestimated even in large regions, whereas those of xB images were close to actual radioactivity concentration. The CV was similar or lower for xB images than that for F3D images but was not decreased with increasing acquisition time for both reconstruction images. The FWHM of xB images was lower than those of F3D images at all acquisition times. The mean SUV values from the first thoracic to fifth lumbar vertebrae for standard- and UHS-xB images were 6.73 ± 0.64 and 6.19 ± 0.87, respectively, showing a strong positive correlation. Results of this phantom study suggest that xB imaging can be obtained in only one-third of the acquisition time without compromising the image quality. The SUV of UHS-xB images can be similar to that of standard-xB images in terms of clinical interpretation.