Preclinical Multimodality Imaging in Vivo

A bird's-eye view of deep learning in bioimage analysis

Deep learning of artificial neural networks has become the de facto standard approach to solving data analysis problems in virtually all fields of science and engineering. Also in biology and medicine, deep learning technologies are fundamentally transforming how we acquire, process, analyze, and interpret data, with potentially far-reaching consequences for healthcare. In this mini-review, we take a bird's-eye view at the past, present, and future developments of deep learning, starting from science at large, to biomedical imaging, and bioimage analysis in particular.

NEMA NU-4 2008 performance evaluation of Xtrim-PET: A prototype SiPM-based preclinical scanner

PURPOSE

Xtrim-PET is a newly designed Silicon Photomultipliers (SiPMs)-based prototype PET scanner dedicated for small laboratory animal imaging. We present the performance evaluation of the Xtrim-PET scanner following NEMA NU-4 2008 standards to help optimizing scanning protocols which can be achieved through standard and reliable system performance characterization.

METHODS

The performance assessment was conducted according to the National Electrical Manufacturers Association (NEMA) NU-4 2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction and image quality. The in vivo imaging capability of the scanner is also showcased through scanning a normal mouse injected with ¹⁸ F-FDG. Furthermore, the performance characteristics of the developed scanner are compared with commercially available systems and current prototypes.

RESULTS

The volumetric spatial resolution at 5 mm radial offset from the central axis of the scanner is 6.81 µl, whereas a peak absolute sensitivity of 2.99% was achieved using a 250-650 keV energy window and a 10 ns timing window. The peak noise-equivalent count rate (NECR) using a mouse-like phantom is 113.18 kcps at 0.34 KBq/cc with 12.5% scatter fraction, whereas the NECR peaked at 82.76 kcps for an activity concentration level of 0.048 KBq/cc with a scatter fraction of 25.8% for rat-like phantom. An excellent uniformity (3.8%) was obtained using NEMA image quality phantom. Recovery coefficients of 90%, 86%, 68%, 40% and 12% were calculated for rod diameters of 5, 4, 3, 2 and 1 mm, respectively. Spill-over ratios for air-filled and water-filled chambers were 35% and 25% without applying any correction for attenuation and Compton scattering effects.

CONCLUSION

Our findings revealed that beyond compactness, lightweight, easy installation and good energy resolution, the Xtrim-PET prototype presents a reasonable performance making it suitable for preclinical molecular imaging-based research.

Characterization of "γ-Eye": a Low-Cost Benchtop Mouse-Sized Gamma Camera for Dynamic and Static Imaging Studies

PURPOSE

Several preclinical imaging systems are commercially available, but their purchase and maintenance costs make them unaffordable for the majority of small- and medium-sized groups. Taking into account the needs of average users, we developed "γ-eye", a mouse-sized, benchtop γ-camera suitable for in vivo scintigraphic imaging.

PROCEDURES

The γ-eye is based on two position-sensitive photomultiplier tubes, coupled to a CsI(Na) pixelated scintillator and a low-energy lead collimator with parallel hexagonal holes.

RESULTS

The spatial resolution of the system is 2 mm at 0 mm. The energy resolution is 26 % at 140 keV and the maximum recorded sensitivity 210 cps/MBq. The system was evaluated in a proof-of-concept animal study, using three different clinical Tc-99m-labeled radiopharmaceuticals. Phantom and animal studies demonstrate its ability to provide semiquantitative results even for short scans.

CONCLUSIONS

Systems' performance, dimensions, and cost make γ-eye a unique solution for efficient whole-body mouse nuclear imaging.

Estimation of subject coregistration errors during multimodal preclinical imaging using separate instruments: origins and avoidance of artifacts

We use high-resolution [Formula: see text] data in multiple experiments to estimate the sources of error during coregistration of images acquired on separate preclinical instruments. In combination with experiments with phantoms, we completed in vivo imaging on mice, aimed at identifying the possible sources of registration errors, caused either by transport of the animal, movement of the animal itself, or methods of coregistration. The same imaging cell was used as a holder for phantoms and animals. For all procedures, rigid coregistration was carried out using a common landmark coregistration system, placed inside the imaging cell. We used the fiducial registration error and the target registration error to analyze the coregistration accuracy. We found that moving an imaging cell between two preclinical devices during a multimodal procedure gives an error of about [Formula: see text] at most. Therefore, it could not be considered a source of coregistration errors. Errors linked to spontaneous movements of the animal increased with time, to nearly 1 mm at most, excepted for body parts that were properly restrained. This work highlights the importance of animal intrinsic movements during a multiacquisition procedure and demonstrates a simple method to identify and quantify the sources of error during coregistration.

An integrated quad-modality molecular imaging system for small animals

We developed a novel integrated quad-modality system that included 3 molecular imaging methods (PET, SPECT, and fluorescence molecular imaging [FMI]) and 1 anatomic imaging modality (CT). This system could study various biologic processes in the same animal using multiple molecular tracers. In addition to the technology development, we also discussed the optimization strategy of the imaging protocols. The performance of this system was tested, and the in vivo animal experiment showed its power to trace 3 different molecular probes in living tissues. Our results demonstrated that this system has a great potential for the preclinical study of diseases.

METHODS

A prototype system integrating PET, SPECT, CT, and a charge-coupled device-based free-space FMI system has been developed. Imaging and fusion capabilities of the system were evaluated by a multimodality phantom. In addition, a mouse disease model with both tumor and inflammation was studied by this system to examine the in vivo performance. The 3 types of molecular probes-(18)F-FDG, [(99m)Tc(HYNIC-3PRGD2)(tricine)(TPPTS)] ((99m)Tc-3PRG2) (HYNIC = 6-hydrazinonicotinyl; TPPTS = trisodium triphenylphosphine-3,3',3″-trisulfonate; 3PRGD2 = PEG4-E[PEG4-c(RGDfK)]2), and 3-(triethoxysilyl) propyl-Cy7-entrapped core-cross-linked polymeric micelle (Cy7-entrapped CCPM) nanoparticles-were used to target 3 different biologic processes in the tumor caused by pulmonary adenocarcinoma A549 cells. Moreover, the strategy to optimize multimodal molecular imaging procedure was studied as well, which could significantly reduce the total imaging time.

RESULTS

The imaging performance has been validated by both phantom and in vivo animal experiments. With this system and optimized imaging protocol, we successfully differentiated diseases that cannot be distinguished by a single molecular imaging modality.

CONCLUSION

We developed a novel quad-modality molecular imaging system that integrated PET, SPECT, FMI, and CT imaging methods to obtain whole-body multimodality images of small animals. The imaging results demonstrated that this system provides more comprehensive information for preclinical biomedical research. With optimized imaging protocols, as well as novel molecular tracers, this quad-modality system can help in the study of the physiology mechanism at an unprecedented level.

Molecular brain imaging in the multimodality era

Multimodality molecular brain imaging encompasses in vivo visualization, evaluation, and measurement of cellular/molecular processes. Instrumentation and software developments over the past 30 years have fueled advancements in multimodality imaging platforms that enable acquisition of multiple complementary imaging outcomes by either combined sequential or simultaneous acquisition. This article provides a general overview of multimodality neuroimaging in the context of positron emission tomography as a molecular imaging tool and magnetic resonance imaging as a structural and functional imaging tool. Several image examples are provided and general challenges are discussed to exemplify complementary features of the modalities, as well as important strengths and weaknesses of combined assessments. Alzheimer's disease is highlighted, as this clinical area has been strongly impacted by multimodality neuroimaging findings that have improved understanding of the natural history of disease progression, early disease detection, and informed therapy evaluation.

Performance evaluation of the FLEX triumph X-PET scanner using the national electrical manufacturers association NU-4 standards

The purpose of this work was to evaluate the performance characteristics of the preclinical X-PET subsystem of the FLEX Triumph PET/CT scanner based on the NU 4-2008 standards of the National Electrical Manufacturers Association (NEMA).

METHODS

The performance parameters evaluated include the spatial resolution, scatter fraction, count losses and random coincidences, sensitivity, and image-quality characteristics. The PET detector array consisted of 11,520 individual bismuth germanate crystals arranged in 48 rings and 180 blocks, with an axial field of view (FOV) of 11.6 cm and a inner ring diameter of 16.5 cm. The spatial resolution was measured with a small (22)Na point source (diameter, 0.25 mm) at different radial offsets from the center. Sensitivity was calculated using the same source by stepping the source axially through the axial FOV of the scanner. Scatter fraction and counting-rate performances were determined using a mouse- and rat-sized phantom with an (18)F line source insert. The NEMA image-quality phantom and rodent imaging were also performed to access the overall imaging capabilities of the scanner.

RESULTS

Tangential spatial resolution in terms of full width at half maximum varied between 2.2 mm at the center of the FOV and 2.3 mm at a radial offset of 2.5 cm. The radial spatial resolution varied between 2.0 at the center and 4.4 mm at a radial offset of 2.3 cm. The peak system absolute sensitivity was 5.9% at the center of the FOV. The absolute system sensitivity was 0.67 counts/s/Bq, and the relative total system sensitivity was 73.9%. The scatter fraction for the mouse-sized phantom was 7.9%, with a peak true counting rate of 168 kilocounts per second (kcps) at 0.3 MBq/mL and a peak noise-equivalent counting rate of 106 kcps at 0.17 MBq/mL. The rat-sized phantom had a scatter fraction of 21%, with a peak true counting rate of 93 kcps at 0.034 MBq/mL and a peak noise-equivalent counting rate of 49 kcps at 0.02 MBq/mL. Recovery coefficients for the image-quality phantom ranged from 0.13 to 0.88.

CONCLUSION

The performance of the X-PET scanner based on the NEMA NU 4-2008 standards was fully characterized. The overall performance demonstrates that the X-PET system is suitable for preclinical research.