Combined PET and MR imaging (PET/MR imaging) has progressed tremendously in recent years. The focus of current research has shifted from technologic challenges to the application of this new multimodal imaging technology in the areas of oncology, cardiology, neurology, and infectious diseases. This article reviews studies in preclinical and clinical translation. The common theme of these initial results is the complementary nature of combined PET/MR imaging that often provides additional insights into biologic systems that were not clearly feasible with just one modality alone. However, in vivo findings require ex vivo validation. Combined PET/MR imaging also triggers a multitude of new developments in image analysis that are aimed at merging and using multimodal information that ranges from better tumor characterization to analysis of metabolic brain networks. The combination of connectomics information that maps brain networks derived from multiparametric MR data with metabolic information from PET can even lead to the formation of a new research field that we would call cometomics that would map functional and metabolic brain networks. These new methodologic developments also call for more multidisciplinarity in the field of molecular imaging, in which close interaction and training among clinicians and a variety of scientists is needed. Mol ecular imaging of small animals for biomedical research is an emerging field (1). It penetrates successfully into areas that are historically dominated by ex vivo molecular biology methods and therefore bears an enormous potential. Exploiting the full range of options of noninvasive visualization and quantification of metabolism, disease-specific dysfunction, therapy response, and cell trafficking requires that specific biomarkers yield information about molecular and functional processes as well as morphologic details. Single-modality imaging, such as stand-alone PET, SPECT, MR imaging, CT, or ultrasound, is often unable to provide the desired comprehensive information. Dedicated small-animal PET/CT and SPECT/CT scanners have been well received in the biomedical imaging sciences and have set the stage for a new combined imaging modality, PET/MR imaging, which has been introduced and successfully applied in biomedical studies (2,3). PET and MR imaging are both distinct modalities offering great versatility for advanced imaging applications in various fields of biomedicine. The combination of these two modalities into a single device merges functional and morphologic information from MR imaging with molecular PET data. The strength of PET lies in its high detection sensitivity and accurate quantification, but PET lacks good spatial resolution and tissue contrast. MR imaging, however, enables highresolution imaging of morphology with good soft-tissue contrast, detects endogenous metabolite distributions using spectroscopy, and allows dynamic acquisition of tissue perfusion and additional functional parameters (4).Thus, PET/MR imaging paves the way for noninvasive imaging to...

The combination of PET and MR imaging forms a powerful new imaging modality, PET/MR. The major advantages of concurrent PET/MR acquisitions range from patient comfort and increased throughput to multiparametric imaging and are evaluated and reviewed in this paper specifically with respect to their applications in research and diagnostics. Alongside the use of PET/MR in the field of preclinical research, this paper illuminates the impact of this new modality in the clinical field in such areas as neurology, oncology, and cardiology. Now that PET/MR technology has matured, attention is needed on standardizing education for nuclear and radiologic technologists and physicians specifically for this combined modality. Furthermore, the impact of this combined modality on health economy needs to be addressed in more detail to further propel its use. More than a decade after the first introduction of prototype preclinical PET/MR systems (1), it is time to critically reflect on the state of PET/ MR technology and its current and future applications in both the preclinical and clinical settings.Although the first ideas about combined PET/MR systems can be traced back to the late 1980s, with patent applications issued more than 20 y ago (2), the technologic evolution of PET/MR was much slower than that of PET/CT, which appeared on the horizon in the mid-1990s and was clinically available as soon as 2000 (3). The main reasons for the slow start of PET/MR into preclinical and clinical practice were mainly the technologic hurdles that needed to be overcome. Combining two imaging systems into a single PET/CT device is relatively straightforward, and the potential mutual interference between the two modalities is limited, unlike PET/MR, which requires a substantial engineering effort. However, the benefits of a combined PET/MR system are at least on a par with PET/CT, and its expected clinical and preclinical potential greatly exceeds the options for PET/CT, specifically in research applications (4). TECHNOLOGIC IMPLICATIONSThe early years of PET/MR development focused on finding alternative approaches to photomultiplier tubes (PMTs)-the traditional PET detectors-which are sensitive to the magnetic field produced by MR systems. Field strengths near the strong main magnetic fields of MR scanners typically are 4.7-21 T preclinically and 1-3 T clinically. The primary approach to coping with the problem of strong magnetic fields was to place the PMTs outside the main magnetic field and link them by long optical fibers to the scintillation crystals (5). Most of these concepts focused on altering solely the PET detection system. However, modifications to the MR system in the form of dedicated split magnets (6) and systems that switched off the MR field during PET acquisition (7) have been presented. Unfortunately, these designs have to cope with some tradeoffs, either on the PET side, where the scintillation light is diminished by the use of long optical fibers, or on the MR side, where the MR performance is degraded by design comprom...

The aim of our study was to create a novel Gaussian mixture modeling (GMM) pipeline to model the complementary information derived from 18 F-FDG PET and diffusion-weighted MRI (DW-MRI) to separate the tumor microenvironment into relevant tissue compartments and follow the development of these compartments longitudinally. Methods: Serial 18 F-FDG PET and apparent diffusion coefficient (ADC) maps derived from DW-MR images of NCI-H460 xenograft tumors were coregistered, and a population-based GMM was implemented on the complementary imaging data. The tumor microenvironment was segmented into 3 distinct regions and correlated with histology. ANCOVA was applied to gauge how well the total tumor volume was a predictor for the ADC and 18 F-FDG, or if ADC was a good predictor of 18 F-FDG for average values in the whole tumor or average necrotic and viable tissues. Results: The coregistered PET/MR images were in excellent agreement with histology, both visually and quantitatively, and allowed for validation of the last-time-point measurements. Strong correlations were found for the necrotic (r 5 0.88) and viable fractions (r 5 0.87) between histology and clustering. The GMM provided probabilities for each compartment with uncertainties expressed as a mixture of tissues in which the resolution of scans was inadequate to accurately separate tissues. The ANCOVA suggested that both ADC and 18 F-FDG in the whole tumor (P 5 0.0009, P 5 0.02) as well as necrotic (P 5 0.008, P 5 0.02) and viable (P 5 0.003, P 5 0.01) tissues were a positive, linear function of total tumor volume. ADC proved to be a positive predictor of 18 F-FDG in the whole tumor (P 5 0.001) and necrotic (P 5 0.02) and viable (P 5 0.0001) tissues. Conclusion: The complementary information of 18 F-FDG and ADC longitudinal measurements in xenograft tumors allows for segmentation into distinct tissues when using the novel GMM pipeline. Leveraging the power of multiparametric PET/MRI in this manner has the potential to take the assessment of disease outcome beyond RECIST and could provide an important impact to the field of precision medicine.

PurposeWe aimed to precisely estimate intra-tumoral heterogeneity using spatially regularized spectral clustering (SRSC) on multiparametric MRI data and compare the efficacy of SRSC with the previously reported segmentation techniques in MRI studies.ProceduresSix NMRI nu/nu mice bearing subcutaneous human glioblastoma U87 MG tumors were scanned using a dedicated small animal 7T magnetic resonance imaging (MRI) scanner. The data consisted of T2 weighted images, apparent diffusion coefficient maps, and pre- and post-contrast T2 and T2* maps. Following each scan, the tumors were excised into 2–3-mm thin slices parallel to the axial field of view and processed for histological staining. The MRI data were segmented using SRSC, K-means, fuzzy C-means, and Gaussian mixture modeling to estimate the fractional population of necrotic, peri-necrotic, and viable regions and validated with the fractional population obtained from histology.ResultsWhile the aforementioned methods overestimated peri-necrotic and underestimated viable fractions, SRSC accurately predicted the fractional population of all three tumor tissue types and exhibited strong correlations (rnecrotic = 0.92, rperi-necrotic = 0.82 and rviable = 0.98) with the histology.ConclusionsThe precise identification of necrotic, peri-necrotic and viable areas using SRSC may greatly assist in cancer treatment planning and add a new dimension to MRI-guided tumor biopsy procedures.Electronic supplementary materialThe online version of this article (doi:10.1007/s11307-016-1009-y) contains supplementary material, which is available to authorized users.

Non-small-cell lung cancer is the most common type of lung cancer and one of the leading causes of cancer-related death worldwide. For this reason, advances in diagnosis and treatment are urgently needed. With the introduction of new, highly innovative hybrid imaging technologies such as PET/CT, staging and therapy response monitoring in lung cancer patients have substantially evolved. In this review, we discuss the role of FDG PET/CT in the management of lung cancer patients and the importance of new emerging imaging technologies and radiotracer developments on the path to personalized medicine.