The recent introduction of high-resolution molecular imaging technology is considered by many experts as a major breakthrough that will potentially lead to a revolutionary paradigm shift in health care and revolutionize clinical practice. This paper intends to balance the capabilities of the two major molecular imaging modalities used in nuclear medicine, namely positron emission tomography (PET) and single photon emission computed tomography (SPECT). The motivations are many-fold: (1) to gain a better understanding of the strengths and limitations of the two imaging modalities in the context of recent and ongoing developments in hardware and software design; (2) to emphasize that certain issues, historically and commonly thought as limitations of one technology, may now instead be viewed as challenges that can be addressed; (3) to point out that current state of the art PET and SPECT scanners can (greatly) benefit from improvements in innovative image reconstruction algorithms; and (4) to identify important areas of research in PET and SPECT imaging that will be instrumental to further improvements in the two modalities. Both technologies are poised to advance molecular imaging and have a direct impact on clinical and research practice to influence the future of molecular medicine.

The Ingenuity TF PET-MRI is a newly released whole-body hybrid PET-MR imaging system with a Philips time-of-flight GEMINI TF PET and Achieva 3T X-series MRI system. Compared to PET-CT, modifications to the positron emission tomography (PET) gantry were made to avoid mutual system interference and deliver uncompromising performance which is equivalent to the standalone systems. The PET gantry was redesigned to introduce magnetic shielding for the photomultiplier tubes (PMTs). Stringent electromagnetic noise requirements of the MR system necessitated the removal of PET gantry electronics to be housed in the PET-MR equipment room. We report the standard NEMA measurements for the PET scanner. PET imaging and performance measurements were done at Geneva University Hospital as described in the NEMA Standards NU 2-2007 manual. The scatter fraction (SF) and noise equivalent count rate (NECR) measurements with the NEMA cylinder (20 cm diameter) were repeated for two larger cylinders (27 cm and 35 cm diameter), which better represent average and heavy patients. A NEMA/IEC torso phantom was used for overall assessment of image quality. The transverse and axial resolution near the center was 4.7 mm. Timing and energy resolution of the PET-MR system were measured to be 525 ps and 12%, respectively. The results were comparable to PET-CT systems demonstrating that the effect of design modifications required on the PET system to remove the harmful effect of the magnetic field on the PMTs was negligible. The absolute sensitivity of this scanner was 7.0 cps kBq(-1), whereas SF was 26%. NECR measurements performed with cylinders having three different diameters, and image quality measurements performed with IEC phantom yielded excellent results. The Ingenuity TF PET-MRI represents the first commercial whole-body hybrid PET-MRI system. The performance of the PET subsystem was comparable to the GEMINI TF PET-CT system using phantom and patient studies. It is conceived that advantages of hybrid PET-MRI will become more evident in the near future.

This review sets out to discuss the foremost applications of artificial intelligence (AI), particularly deep learning (DL) algorithms, in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging. To this end, the underlying limitations/challenges of these imaging modalities are briefly discussed followed by a description of AI-based solutions proposed to address these challenges. This review will focus on mainstream generic fields, including instrumentation, image acquisition/formation, image reconstruction and low-dose/fast scanning, quantitative imaging, image interpretation (computer-aided detection/diagnosis/prognosis), as well as internal radiation dosimetry. A brief description of deep learning algorithms and the fundamental architectures used for these applications is also provided. Finally, the challenges, opportunities, and barriers to full-scale validation and adoption of AI-based solutions for improvement of image quality and quantitative accuracy of PET and SPECT images in the clinic are discussed.

Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking.