OBJECTIVES Accurate estimation of radiopharmaceutical uptake in the brain is difficult because of count statistics, low spatial resolution, and smoothing filter. The aim of this study was to assess the counting rate performance of PET scanners and the image quality with different combinations of high-resolution image reconstruction algorithms in brain F-2-fluorodeoxy-D-glucose (F-FDG)-PET. MATERIALS AND METHODS Using 23 patient studies, we analyzed the coincidence rates of true and random, random fraction, and the noise equivalent counts per axial length (NECpatient) in brain and liver bed positions. The reconstruction algorithms were combined with baseline ordered subsets expectation maximization, Gaussian filter (GF), point spread function (PSF), and time-of-flight (TOF). The image quality of the brain cortex was quantitatively evaluated with respect to spatial resolution, contrast, and signal-to-noise ratio (SNR). RESULTS The true coincidence rate in the brain was higher by 1.86 times and the random coincidence rate was lower by 0.61 times compared with that in the liver. In the brain, random fraction was lower and NECpatient was higher than that of the liver. Although GF improved the SNR, spatial resolution and contrast were reduced by 12 and 11%, respectively (P<0.01). PSF improved spatial resolution and SNR by 11 and 53%, respectively (P<0.01), and TOF improved SNR by ∼23% (P<0.01). CONCLUSION We have demonstrated that a high-resolution image reconstruction algorithm for brain F-FDG-PET is promising without the use of a GF because of high true coincidence counts and that combined with PSF and TOF is optimal for obtaining a better SNR of the image.

Clinical validation of high-resolution image reconstruction algorithms in brain 18F-FDG-PET: effect of incorporating Gaussian filter, point spread function, and time-of-flight

Precise assessment of lymph node metastases is critical to the treatment outcome and overall survival of patients with head and neck squamous cell carcinoma (HNSCC). The purpose of this study was to investigate the effect of time-of-flight (TOF) technique on the diagnostic performance of 18F-FDG PET/CT for assessment of lymph node metastases in HNSCC patients. Methods: In 39 patients with an initial diagnosis of HNSCC, preoperative staging 18F-FDG PET/CT was performed to assess lymph node metastases before surgery and histologic verification. Potential lymph node metastases were evaluated and documented separately for the right and left neck in accordance with the head and neck lymph node level classification. Two experienced readers measured lesion volume and uptake for every PET-positive lymph node. Sensitivity, specificity, image quality, and the PET characterization of the lesion (benign or malignant) were compared between different reconstruction methods (TOF PET and standard high-definition PET) and matrices for both readers. Results: TOF PET significantly increased the maximal standardized uptake value (SUVmax) but had no significant effect on lesion volume. However, a higher SUVmax did not result in a significant increase in small-lesion detection. Sensitivity and image quality were slightly improved with TOF PET but not significantly so. Matrix, on the other hand, had a significant effect on detected lesion numbers, sensitivity, and image quality. Conclusion: For preoperative assessment of lymph node metastases in HNSCC, 18F-FDG PET/CT using TOF technique increases SUVmax in lesions and improves image quality but has no significant impact on small-lesion detectability.

https://tech.snmjournals.org/content/jnmt/42/3/181.full.pdf

Effect of Time-of-Flight Technique on the Diagnostic Performance of 18F-FDG PET/CT for Assessment of Lymph Node Metastases in Head and Neck Squamous Cell Carcinoma

Comparison of applied dose and image quality in staging CT of neuroendocrine tumor patients using standard filtered back projection and adaptive statistical iterative reconstruction.

Given the constant pressure to increase patient throughput while respecting radiation protection, global body PET image quality (IQ) is not satisfactory in all patients. We first studied the association between IQ and other variables, in particular body habitus, on a digital PET/CT. Second, to improve and homogenize IQ, we evaluated a deep learning PET denoising solution (Subtle PETTM) using convolutional neural networks. We analysed retrospectively in 113 patients visual IQ (by a 5-point Likert score in two readers) and semi-quantitative IQ (by the coefficient of variation in the liver, CVliv) as well as lesion detection and quantification in native and denoised PET. In native PET, visual and semi-quantitative IQ were lower in patients with larger body habitus (p < 0.0001 for both) and in men vs. women (p ≤ 0.03 for CVliv). After PET denoising, visual IQ scores increased and became more homogeneous between patients (4.8 ± 0.3 in denoised vs. 3.6 ± 0.6 in native PET; p < 0.0001). CVliv were lower in denoised PET than in native PET, 6.9 ± 0.9% vs. 12.2 ± 1.6%; p < 0.0001. The slope calculated by linear regression of CVliv according to weight was significantly lower in denoised than in native PET (p = 0.0002), demonstrating more uniform CVliv. Lesion concordance rate between both PET series was 369/371 (99.5%), with two lesions exclusively detected in native PET. SUVmax and SUVpeak of up to the five most intense native PET lesions per patient were lower in denoised PET (p < 0.001), with an average relative bias of −7.7% and −2.8%, respectively. DL-based PET denoising by Subtle PETTM allowed [18F]FDG PET global image quality to be improved and homogenized, while maintaining satisfactory lesion detection and quantification. DL-based denoising may render body habitus adaptive PET protocols unnecessary, and pave the way for the improvement and homogenization of PET modalities.

/pdf/deep-learning-denoising-improves-and-homogenizes-patient-18f-2j0r4ven.pdf

Deep Learning Denoising Improves and Homogenizes Patient [18F]FDG PET Image Quality in Digital PET/CT

Background: A prospective study was performed to assess standard uptake value (SUV)-level based 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) lymph node staging in 33 patients with oropharyngeal squamous cell cancer (OSCC) out of a total of 99 patients with head-and-neck squamous cell cancer (HNSCC) and the role of nodal molecular marker expression in diagnostic outcome prediction. Methods: Preoperative nodal PET/CT staging in 123 lymph nodes was correlated with postoperative lymph node histology, which served as gold standard. Tissue samples were prepared for immunohistochemistry of the excised lymph nodes. Results: The negative and positive predictive values (NPV and PPV) of PET for correct lymph node assessment were 100% and 93%, respectively. There was a significant association between SUVmax and lymph node histology (p < 0.0001) and a significant linear correlation between SUVmax and nodal size (Pearson's correlation coefficient r = 0.61336, p < 0.0001). The molecular marker E-Cadherin was significantly overexpressed in lymph node metastases (p < 0.0001). Benign lymph nodes showed significant 2-fold Bcl2 overexpression (p < 0.0001). However, the molecular marker expression profiles were inhomogeneous and did not allow valuable diagnostic outcome prediction. Conclusions: SUV level-based 18F-FDG-PET/CT lymph node assessment in OSCC still has to be considered as the most established and reliable staging tool. Lymph node molecular marker expression profiles need to be investigated further as they currently do not sufficiently contribute to therapy decision-making.

/pdf/18f-fluorodeoxyglucose-uptake-level-based-lymph-node-staging-6uw08dofo3.pdf

18F-fluorodeoxyglucose uptake level-based lymph node staging in oropharyngeal squamous cell cancer--role of molecular marker expression on diagnostic outcome.

Therapy outcome and overall survival in patients with head and neck squamous cell carcinoma (HNSCC) is influenced by precise localization of the primary tumor and detection of lymph node metastasis involvement at the time of initial diagnosis. Only accurate preoperative staging can improve primary tumor response and avoid early locoregional recurrence with lymph node metastases. The purpose of this study was the optimization of reconstruction parameters in high-definition PET/CT for the improved diagnostic assessment of lymph node metastases. Methods: In the experimental study, image contrast and signal-to-noise ratio were evaluated using a Jaszczak phantom. In the clinical study, 54 patients underwent head and neck imaging on a PET/CT scanner. Diagnostic findings were correlated with postoperative histopathology. For the 54 patients, 123 lymph nodes were evaluated on PET and histologically correlated with the neck dissection specimen. Forty-one lymph nodes were benign, and 82 findings were confirmed as being malignant. Both experimental and clinical studies were reconstructed into a 200 × 200 matrix using a 3-dimensional iterative reconstruction algorithm (ordered-subset expectation maximization [OSEM], 3 iterative steps, 24 subsets). Postfiltering with a 3-dimensional gaussian filter was applied. To study the effect of smoothing filter strength on the diagnostic accuracy of lymph node metastasis detection, 3 different cutoffs—1, 3, and 6 mm in full width at half maximum—were used to perform reconstructions. Results: Phantom studies showed that images reconstructed with 3-mm gaussian postfiltering gained a higher image quality and signal-to-noise ratio. Overall sensitivities for correctly diagnosed lymph nodes were best in 3-mm postfiltered images. Best results for true-positive lymph node findings were achieved with 3-mm postfiltering. With 1-mm postfiltering, accurate lesion detection was not improved, because increasing sensitivity (95% true-positive) correlated with decreasing specificity (12% false-positive). Conclusion: For lymph node assessment on a high-resolution PET/CT scanner, we consider the OSEM algorithm with 3 iterations and 24 subsets, combined with 3-dimensional 3-mm gaussian postfiltering, to be optimal. The continuous application of presently established PET protocols in patients with HNSCC will prove whether current acquisition and reconstruction methods are valuable and should be maintained.

https://tech.snmjournals.org/content/jnmt/41/1/19.full.pdf

Effect of Reconstruction Parameters in High-Definition PET/CT on Assessment of Lymph Node Metastases in Head and Neck Squamous Cell Carcinoma

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Effect of Reconstruction Parameters in High-Definition PET/CT on Assessment of Lymph Node Metastases in Head and Neck Squamous Cell Carcinoma