Overview of positron emission tomography, hybrid positron emission tomography instrumentation, and positron emission tomography quantification

Post-acquisition standardization of positron emission tomography images

Purpose

Tissue radiotracer activity measured from positron emission tomography (PET) images is an important biomarker that is clinically utilized for diagnosis, staging, prognostication, and treatment response assessment in patients with cancer and other clinical disorders. Using PET image values to define a normal range of metabolic activity for quantification purposes is challenging due to variations in patient-related factors and technical factors. Although the formulation of standardized uptake value (SUV) has compensated for some of these variabilities, significant non-standardness still persists. We propose an image processing method to substantially mitigate these variabilities.

Methods

The standardization method is similar for activity concentration (AC) PET and SUV PET images with some differences and consists of two steps. The calibration step is performed only once for each of AC PET or SUV PET, employs a set of images of normal subjects, and requires a reference object, while the transformation step is executed for each patient image to be standardized. In the calibration step, a standardized scale is determined along with 3 key image intensity landmarks defined on it including the minimum percentile intensitys min , median intensitys m , and high percentile intensitys max . s min ands m are estimated based on image intensities within the body region in the normal calibration image set. The optimal value of the maximum percentile β corresponding to the intensitys max is estimated via an optimization process by using the reference object to optimally separate the highly variable high uptake values from the normal uptake intensities. In the transformation step, the first two landmarks-the minimum percentile intensityp α ( I ) , and the median intensityp m ( I ) -are found for the given image I for the body region, and the high percentile intensityp β ( I ) is determined corresponding to the optimally estimated high percentile value β . Subsequently, intensities of I are mapped to the standard scale piecewise linearly for different segments. We employ three strategies for evaluation and comparison with other standardization methods: (i) comparing coefficient of variationC V O of mean intensity within test objects O across different normal test subjects before and after standardization; (ii) comparing mean absolute difference (MD O ) of mean intensity within test objects O across different subjects in repeat scans before and after standardization; (iii) comparingC V O of mean intensity across different normal subjects before and after standardization where the scans came from different brands of scanners.

Results

Our data set consisted of 84 FDG-PET/CT scans of the body torso including 38 normal subjects and two repeat-scans of 23 patients. We utilized one of two objects-liver and spleen-as a reference object and the other for testing. The proposed standardization method reducedC V O andMD O by a factor of 3-8 in comparison to other standardization methods and no standardization. Upon standardization by our method, the image intensities (both for AC and SUV) from two different brands of scanners become statistically indistinguishable, while without standardization, they differ significantly and by a factor of 3-9.

Conclusions

The proposed method is automatic, outperforms current standardization methods, and effectively overcomes the residual variation left over in SUV and inter-scanner variations.

Disease quantification on PET/CT images without explicit object delineation

PURPOSE

The derivation of quantitative information from images in a clinically practical way continues to face a major hurdle because of image segmentation challenges. This paper presents a novel approach, called automatic anatomy recognition-disease quantification (AAR-DQ), for disease quantification (DQ) on positron emission tomography/computed tomography (PET/CT) images. This approach explores how to decouple DQ methods from explicit dependence on object (e.g., organ) delineation through the use of only object recognition results from our recently developed automatic anatomy recognition (AAR) method to quantify disease burden.

METHOD

The AAR-DQ process starts off with the AAR approach for modeling anatomy and automatically recognizing objects on low-dose CT images of PET/CT acquisitions. It incorporates novel aspects of model building that relate to finding an optimal disease map for each organ. The parameters of the disease map are estimated from a set of training image data sets including normal subjects and patients with metastatic cancer. The result of recognition for an object on a patient image is the location of a fuzzy model for the object which is optimally adjusted for the image. The model is used as a fuzzy mask on the PET image for estimating a fuzzy disease map for the specific patient and subsequently for quantifying disease based on this map. This process handles blur arising in PET images from partial volume effect entirely through accurate fuzzy mapping to account for heterogeneity and gradation of disease content at the voxel level without explicitly performing correction for the partial volume effect. Disease quantification is performed from the fuzzy disease map in terms of total lesion glycolysis (TLG) and standardized uptake value (SUV) statistics. We also demonstrate that the method of disease quantification is applicable even when the "object" of interest is recognized manually with a simple and quick action such as interactively specifying a 3D box ROI. Depending on the degree of automaticity for object and lesion recognition on PET/CT, DQ can be performed at the object level either semi-automatically (DQ-MO) or automatically (DQ-AO), or at the lesion level either semi-automatically (DQ-ML) or automatically.

RESULTS

We utilized 67 data sets in total: 16 normal data sets used for model building, and 20 phantom data sets plus 31 patient data sets (with various types of metastatic cancer) used for testing the three methods DQ-AO, DQ-MO, and DQ-ML. The parameters of the disease map were estimated using the leave-one-out strategy. The organs of focus were left and right lungs and liver, and the disease quantities measured were TLG, SUV_Mean, and SUV_Max. On phantom data sets, overall error for the three parameters were approximately 6%, 3%, and 0%, respectively, with TLG error varying from 2% for large "lesions" (37 mm diameter) to 37% for small "lesions" (10 mm diameter). On patient data sets, for non-conspicuous lesions, those overall errors were approximately 19%, 14% and 0%; for conspicuous lesions, these overall errors were approximately 9%, 7%, 0%, respectively, with errors in estimation being generally smaller for liver than for lungs, although without statistical significance.

CONCLUSIONS

Accurate disease quantification on PET/CT images without performing explicit delineation of lesions is feasible following object recognition. Method DQ-MO generally yields more accurate results than DQ-AO although the difference is statistically not significant. Compared to current methods from the literature, almost all of which focus only on lesion-level DQ and not organ-level DQ, our results were comparable for large lesions and were superior for smaller lesions, with less demand on training data and computational resources. DQ-AO and even DQ-MO seem to have the potential for quantifying disease burden body-wide routinely via the AAR-DQ approach.

Non-invasive imaging modalities to study neurodegenerative diseases of aging brain

The aim of this article is to highlight current approaches for imaging elderly brain, indispensable for cognitive neuroscience research with emphasis on the basic physical principles of various non-invasive neuroimaging techniques. The first part of this article presents a quick overview of the primary non-invasive neuroimaging modalities used by cognitive neuroscientists such as transcranial magnetic stimulation (TMS), transcranial electrical stimulation (tES), electroencephalography (EEG), magnetoencephalography (MEG), single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance spectroscopic imaging (MRSI), Profusion imaging, functional magnetic resonance imaging (fMRI), near infrared spectroscopy (NIRS) and diffusion tensor imaging (DTI) along with tractography and connectomics. The second part provides a comprehensive overview of different multimodality imaging techniques for various cognitive neuroscience studies of aging brain.

A Study of the Feasibility of FDG-PET/CT to Systematically Detect and Quantify Differential Metabolic Effects of Chronic Tobacco Use in Organs of the Whole Body-A Prospective Pilot Study

RATIONALE AND OBJECTIVES

The aim of this study was to assess the feasibility of ¹⁸F-fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT) to systematically detect and quantify differential effects of chronic tobacco use in organs of the whole body.

MATERIALS AND METHODS

Twenty healthy male subjects (10 nonsmokers and 10 chronic heavy smokers) were enrolled. Subjects underwent whole-body FDG-PET/CT, diagnostic unenhanced chest CT, mini-mental state examination, urine testing for oxidative stress, and serum testing. The organs of interest (thyroid, skin, skeletal muscle, aorta, heart, lung, adipose tissue, liver, spleen, brain, lumbar spinal bone marrow, and testis) were analyzed on FDG-PET/CT images to determine their metabolic activities using standardized uptake value (SUV) or metabolic volumetric product (MVP). Measurements were compared between subject groups using two-sample t tests or Wilcoxon rank-sum tests as determined by tests for normality. Correlational analyses were also performed.

RESULTS

FDG-PET/CT revealed significantly decreased metabolic activity of lumbar spinal bone marrow (MVPmean: 29.8 ± 9.7 cc vs 40.8 ± 11.6 cc, P = 0.03) and liver (SUVmean: 1.8 ± 0.2 vs 2.0 ± 0.2, P = 0.049) and increased metabolic activity of visceral adipose tissue (SUVmean: 0.35 ± 0.10 vs 0.26 ± 0.06, P = 0.02) in chronic smokers compared to nonsmokers. Normalized visceral adipose tissue volume was also significantly decreased (P = 0.04) in chronic smokers. There were no statistically significant differences in the metabolic activity of other assessed organs.

CONCLUSIONS

Subclinical organ effects of chronic tobacco use are detectable and quantifiable on FDG-PET/CT. FDG-PET/CT may, therefore, play a major role in the study of systemic toxic effects of tobacco use in organs of the whole body for clinical or research purposes.

Metabolic effects of pulmonary obstruction on myocardial functioning: a pilot study using multiple time-point 18F-FDG-PET imaging

RATIONALE

The aim of this study was to evaluate fluorine-18 fluorodeoxyglucose (18F-FDG) uptake in the right ventricle (RV) of patients with chronic obstructive pulmonary disease (COPD) and to characterize the variability of 18F-FDG uptake in the RV at different time points following radiotracer administration using PET/computerized tomography (CT). Impaired RV systolic function, RV hypertrophy, and RV dilation are associated with increases in mean pulmonary arterial pressure in patients with COPD. Metabolic changes in the RV using 18F-FDG-PET images 2 and 3 h after tracer injection have not yet been investigated.

METHODS

Twenty-five patients with clinical suspicion of lung cancer underwent 18F-FDG-PET/CT imaging at 1, 2, and 3 h after tracer injection. Standardized uptake values (SUVs) and volumes of RV were recorded from transaxial sections to quantify the metabolic activity.

RESULTS

The SUV of RV was higher in patients with COPD stages 1-3 as compared with that in patients with COPD stage 0. RV SUV was inversely correlated with FEV1/FVC pack-years of smoking at 1 h after 18F-FDG injection. In the majority of patients, 18F-FDG activity in RV decreased over time. There was no significant difference in the RV myocardial free wall and chamber volume on the basis of COPD status.

CONCLUSION

The severity of lung obstruction and pack-years of smoking correlate with the level of 18F-FDG uptake in the RV myocardium, suggesting that there may be metabolic changes in the RV associated with lung obstruction that can be detected noninvasively using 18F-FDG-PET/CT. Multiple time-point images of the RV did not yield any additional value in this study.

The neurobiology of eating disorders--a clinical perspective

OBJECTIVE

To provide a neurobiological basis of eating disorders for clinicians and to enlighten how comparing neurobiology and eating disorders with neurobiology of other psychiatric illnesses can improve treatment protocols.

METHOD

A selective review on the neurobiology of eating disorders. The article focuses on clinical research on humans with consideration of the anatomical, neural, and molecular basis of eating disorders.

RESULTS

The neurobiology of people with eating disorders is altered. Many of the neurobiological regions, receptors, and chemical substrates that are affected in other mental illnesses also play an important role in eating disorders. More knowledge about the neurobiological overlap between eating disorders and other psychiatric populations will help when developing treatment protocols not the least regarding that comorbidity is common in patients with EDs.

CONCLUSION

Knowledge about the underlying neurobiology of eating disorders will improve treatment intervention and will benefit from comparisons with other mental illnesses and their treatments.

Combined MTOR and autophagy inhibition: phase I trial of hydroxychloroquine and temsirolimus in patients with advanced solid tumors and melanoma

The combination of temsirolimus (TEM), an MTOR inhibitor, and hydroxychloroquine (HCQ), an autophagy inhibitor, augments cell death in preclinical models. This phase 1 dose-escalation study evaluated the maximum tolerated dose (MTD), safety, preliminary activity, pharmacokinetics, and pharmacodynamics of HCQ in combination with TEM in cancer patients. In the dose escalation portion, 27 patients with advanced solid malignancies were enrolled, followed by a cohort expansion at the top dose level in 12 patients with metastatic melanoma. The combination of HCQ and TEM was well tolerated, and grade 3 or 4 toxicity was limited to anorexia (7%), fatigue (7%), and nausea (7%). An MTD was not reached for HCQ, and the recommended phase II dose was HCQ 600 mg twice daily in combination with TEM 25 mg weekly. Other common grade 1 or 2 toxicities included fatigue, anorexia, nausea, stomatitis, rash, and weight loss. No responses were observed; however, 14/21 (67%) patients in the dose escalation and 14/19 (74%) patients with melanoma achieved stable disease. The median progression-free survival in 13 melanoma patients treated with HCQ 1200mg/d in combination with TEM was 3.5 mo. Novel 18-fluorodeoxyglucose positron emission tomography (FDG-PET) measurements predicted clinical outcome and provided further evidence that the addition of HCQ to TEM produced metabolic stress on tumors in patients that experienced clinical benefit. Pharmacodynamic evidence of autophagy inhibition was evident in serial PBMC and tumor biopsies only in patients treated with 1200 mg daily HCQ. This study indicates that TEM and HCQ is safe and tolerable, modulates autophagy in patients, and has significant antitumor activity. Further studies combining MTOR and autophagy inhibitors in cancer patients are warranted.

Lost in Translation (LiT): IUPHAR Review 6

Translational medicine is a roller coaster with occasional brilliant successes and a large majority of failures. Lost in Translation 1 ('LiT1'), beginning in the 1950s, was a golden era built upon earlier advances in experimental physiology, biochemistry and pharmacology, with a dash of serendipity, that led to the discovery of many new drugs for serious illnesses. LiT2 saw the large-scale industrialization of drug discovery using high-throughput screens and assays based on affinity for the target molecule. The links between drug development and university sciences and medicine weakened, but there were still some brilliant successes. In LiT3, the coverage of translational medicine expanded from molecular biology to drug budgets, with much greater emphasis on safety and official regulation. Compared with R&D expenditure, the number of breakthrough discoveries in LiT3 was disappointing, but monoclonal antibodies for immunity and inflammation brought in a new golden era and kinase inhibitors such as imatinib were breakthroughs in cancer. The pharmaceutical industry is trying to revive the LiT1 approach by using phenotypic assays and closer links with academia. LiT4 faces a data explosion generated by the genome project, GWAS, ENCODE and the 'omics' that is in danger of leaving LiT4 in a computerized cloud. Industrial laboratories are filled with masses of automated machinery while the scientists sit in a separate room viewing the results on their computers. Big Data will need Big Thinking in LiT4 but with so many unmet medical needs and so many new opportunities being revealed there are high hopes that the roller coaster will ride high again.

FDG-PET/CT assessment of differential chemotherapy effects upon skeletal muscle metabolism in patients with melanoma

OBJECTIVES

To quantify the differential effects of chemotherapy on the metabolic activity of skeletal muscle in vivo using molecular imaging with [18F]-fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT).

METHODS

In this retrospective study, 21 subjects with stage IV melanoma who underwent pre- and post-chemotherapy whole-body FDG-PET/CT imaging were included. The mean standardized uptake value (SUVmean) of 8 different skeletal muscles was measured per subject. Pre- and post-treatment measurements were then averaged across all subjects for each muscle and compared for statistically significant differences between the muscles and following different chemotherapy regimens including dacarbazine (DTIC) and temozolomide (TMZ).

RESULTS

Analysis of FDG-PET/CT images reliably detected changes in skeletal muscle metabolic activity based on muscle location. The percent change in metabolic activity of each skeletal muscle in each subject following chemotherapy was observed to be related to the type of chemotherapy received. Subjects receiving DTIC generally had a decrease in metabolic activity of all muscle groups, whereas subjects receiving TMZ generally had an increase in muscle activity of all muscle groups.

CONCLUSION

FDG-PET/CT can reveal baseline metabolic differences between different muscles of the body. Different chemotherapies are associated with differential changes in the metabolic activity of skeletal muscle, which can be detected and quantified with FDG-PET/CT.