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 NU2-2007 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.

Historically, anatomical CT and MR images were used to delineate the gross tumour volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern radiation therapy units and the widespread availability of combined PET/CT scanners stimulated the development of biological PET imaging-guided radiation therapy treatment planning with the aim to produce highly conformal radiation dose distribution to the tumour. One of the most difficult issues facing PET-based treatment planning is the accurate delineation of target regions from typical blurred and noisy functional images. The major problems encountered are image segmentation and imperfect system response function. Image segmentation is defined as the process of classifying the voxels of an image into a set of distinct classes. The difficulty in PET image segmentation is compounded by the low spatial resolution and high noise characteristics of PET images. Despite the difficulties and known limitations, several image segmentation approaches have been proposed and used in the clinical setting including thresholding, edge detection, region growing, clustering, stochastic models, deformable models, classifiers and several other approaches. A detailed description of the various approaches proposed in the literature is reviewed. Moreover, we also briefly discuss some important considerations and limitations of the widely used techniques to guide practitioners in the field of radiation oncology. The strategies followed for validation and comparative assessment of various PET segmentation approaches are described. Future opportunities and the current challenges facing the adoption of PET-guided delineation of target volumes and its role in basic and clinical research are also addressed.

Purpose The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application. Approach A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed. Findings A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol. Conclusions Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to ...

Purpose In this article, we discuss dynamic whole-body (DWB) positron emission tomography (PET) as an imaging tool with significant clinical potential, in relation to conventional standard uptake value (SUV) imaging. Background DWB PET involves dynamic data acquisition over an extended axial range, capturing tracer kinetic information that is not available with conventional static acquisition protocols. The method can be performed within reasonable clinical imaging times, and enables generation of multiple types of PET images with complementary information in a single imaging session. Importantly, DWB PET can be used to produce multi-parametric images of (i) Patlak slope (influx rate) and (ii) intercept (referred to sometimes as Bdistribution volume^), while also providing (iii) a conventional 'SUV-equivalent' image for certain protocols. Results We provide an overview of ongoing efforts (primarily focused on FDG PET) and discuss potential clinically relevant applications. Conclusion Overall, the framework of DWB imaging [applicable to both PET/CT(computed tomography) and PET/MRI (magnetic resonance imaging)] generates quantitative measures that may add significant value to conventional SUV imagederived measures, with limited pitfalls as we also discuss in this work.