Static whole body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single bed-coverage limiting the axial field-of-view to ~15–20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole body PET acquisition protocol of ~45min total length is presented, composed of (i) an initial 6-min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (6 passes x 7 bed positions, each scanned for 45sec). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares (OLS) Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of 10 different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole-body. In addition, the total acquisition length can be reduced from 45min to ~35min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error (MSE) and the CNR metrics, resulting in enhanced task-based imaging.

There has been no established qualitative system of interpretation for therapy response assessment using PET/CT for head and neck cancers. The objective of this study was to validate the Hopkins interpretation system to assess therapy response and survival outcome in head and neck squamous cell cancer patients (HNSCC). Methods The study included 214 biopsy-proven HNSCC patients who underwent a posttherapy PET/CT study, between 5 and 24 wk after completion of treatment. The median follow-up was 27 mo. PET/CT studies were interpreted by 3 nuclear medicine physicians, independently. The studies were scored using a qualitative 5-point scale, for the primary tumor, for the right and left neck, and for overall assessment. Scores 1, 2, and 3 were considered negative for tumors, and scores 4 and 5 were considered positive for tumors. The Cohen κ coefficient (κ) was calculated to measure interreader agreement. Overall survival (OS) and progression-free survival (PFS) were analyzed by Kaplan–Meier plots with a Mantel–Cox log-rank test and Gehan Breslow Wilcoxon test for comparisons. Results Of the 214 patients, 175 were men and 39 were women. There was 85.98%, 95.33%, 93.46%, and 87.38% agreement between the readers for overall, left neck, right neck, and primary tumor site response scores, respectively. The corresponding κ coefficients for interreader agreement between readers were, 0.69–0.79, 0.68–0.83, 0.69–0.87, and 0.79–0.86 for overall, left neck, right neck, and primary tumor site response, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the therapy assessment were 68.1%, 92.2%, 71.1%, 91.1%, and 86.9%, respectively. Cox multivariate regression analysis showed human papillomavirus (HPV) status and PET/CT interpretation were the only factors associated with PFS and OS. Among the HPV-positive patients (n = 123), there was a significant difference in PFS (hazard ratio [HR], 0.14; 95% confidence interval, 0.03–0.57; P = 0.0063) and OS (HR, 0.01; 95% confidence interval, 0.00–0.13; P = 0.0006) between the patients who had a score negative for residual tumor versus positive for residual tumor. A similar significant difference was observed in PFS and OS for all patients. There was also a significant difference in the PFS of patients with PET-avid residual disease in one site versus multiple sites in the neck (HR, 0.23; log-rank P = 0.004). Conclusion The Hopkins 5-point qualitative therapy response interpretation criteria for head and neck PET/CT has substantial interreader agreement and excellent negative predictive value and predicts OS and PFS in patients with HPV-positive HNSCC.

In patients with different subtypes of dementia, FDG PET/CT shows distinct spatial patterns of metabolism in the brain and can help clinicians to make a reasonably accurate and early diagnosis for appropriate management or prognosis.

Standardized uptake value (SUV) normalized by lean body mass ([LBM] SUL) is becoming a popular metric for quantitative assessment of clinical PET. Sex-specific quantitative effects of different LBM formulations on liver SUV have not been well studied. Methods 18F-FDG PET/CT scans from 1,033 consecutive adult (501 women, 532 men) studies were reviewed. Liver SUV was measured with a 3-cm-diameter spheric region of interest in the right hepatic lobe and corrected for LBM using the sex-specific James and Janmahasatian formulations. Results Body weight was 71.0 ± 20.7 kg (range, 18.0–175.0 kg) and 82.9 ± 18.6 kg (range, 23.0–159.0 kg) for women and men, respectively. SUV, based on body weight, has a significantly positive correlation with weight for both women (r = 0.58, P < 0.0001) and men (r = 0.54, P < 0.0001). This correlation is reduced in men (r = 0.11, P = 0.01) and becomes negative for women (r = −0.35, P = 0.0001) with the James formulation of SUL. This negative correlation was eliminated when the very obese women (body mass index ≥ 35) were excluded from the analysis (r = 0.13, P = 0.8). The Janmahasatian formulation annuls the correlation between SUL and weight for women (r = 0.04, P = 0.4) and decreases it for men (r = 0.13, P = 0.003). Conclusion Hepatic correction with the more common James formulation for body lean mass breaks down and shows low SUL values in very obese patients. The adoption of the Janmahasatian formula for estimation of LBM in modern PET scanners and display workstations is recommended, in view of the increasing frequency of obesity.